Overview

Dataset statistics

Number of variables133
Number of observations8316
Missing cells618
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory58.0 MiB
Average record size in memory7.1 KiB

Variable types

Categorical126
Numeric7

Alerts

Año has constant value "2000" Constant
entidad has constant value "26" Constant
nom_ent has constant value "Sonora" Constant
nom_mun has a high cardinality: 73 distinct values High cardinality
nom_loc has a high cardinality: 6155 distinct values High cardinality
pmascul has a high cardinality: 531 distinct values High cardinality
pfemeni has a high cardinality: 511 distinct values High cardinality
pob0_4 has a high cardinality: 275 distinct values High cardinality
p5_mas has a high cardinality: 646 distinct values High cardinality
pob6_14 has a high cardinality: 350 distinct values High cardinality
pob12_ has a high cardinality: 605 distinct values High cardinality
pob15_ has a high cardinality: 584 distinct values High cardinality
pob15_17 has a high cardinality: 218 distinct values High cardinality
pob15_24 has a high cardinality: 355 distinct values High cardinality
pobf15_49 has a high cardinality: 384 distinct values High cardinality
pob18_ has a high cardinality: 568 distinct values High cardinality
pmasc18_ has a high cardinality: 439 distinct values High cardinality
pfemen18_ has a high cardinality: 412 distinct values High cardinality
psderss has a high cardinality: 586 distinct values High cardinality
pcderss has a high cardinality: 440 distinct values High cardinality
pderimss has a high cardinality: 403 distinct values High cardinality
pderiste has a high cardinality: 200 distinct values High cardinality
pnacent has a high cardinality: 646 distinct values High cardinality
pnacoent has a high cardinality: 272 distinct values High cardinality
p5_res95 has a high cardinality: 663 distinct values High cardinality
p5_reso95 has a high cardinality: 167 distinct values High cardinality
pcondisc has a high cardinality: 145 distinct values High cardinality
pcdismot has a high cardinality: 109 distinct values High cardinality
pcdisaud has a high cardinality: 68 distinct values High cardinality
pcdisvis has a high cardinality: 88 distinct values High cardinality
pcdismen has a high cardinality: 75 distinct values High cardinality
psindisc has a high cardinality: 681 distinct values High cardinality
p6_14slee has a high cardinality: 336 distinct values High cardinality
p6_14nlee has a high cardinality: 154 distinct values High cardinality
p15_alfab has a high cardinality: 561 distinct values High cardinality
p15_analf has a high cardinality: 200 distinct values High cardinality
p5_asiesc has a high cardinality: 116 distinct values High cardinality
p5_naesc has a high cardinality: 98 distinct values High cardinality
p6_14aesc has a high cardinality: 349 distinct values High cardinality
p6_14naesc has a high cardinality: 125 distinct values High cardinality
p15_17aesc has a high cardinality: 168 distinct values High cardinality
p15_24aesc has a high cardinality: 193 distinct values High cardinality
p15_24nesc has a high cardinality: 305 distinct values High cardinality
p15_sinstr has a high cardinality: 208 distinct values High cardinality
p15_sprima has a high cardinality: 344 distinct values High cardinality
p15_cprima has a high cardinality: 302 distinct values High cardinality
p15_pospri has a high cardinality: 409 distinct values High cardinality
p15_ssecu has a high cardinality: 198 distinct values High cardinality
p15_csecu has a high cardinality: 292 distinct values High cardinality
p15_sinsec has a high cardinality: 476 distinct values High cardinality
p15_consec has a high cardinality: 339 distinct values High cardinality
p15_cmedss has a high cardinality: 265 distinct values High cardinality
p18_smedsu has a high cardinality: 522 distinct values High cardinality
p18_cmedsu has a high cardinality: 214 distinct values High cardinality
p18_csuper has a high cardinality: 164 distinct values High cardinality
psolter12_ has a high cardinality: 388 distinct values High cardinality
pcasada12_ has a high cardinality: 480 distinct values High cardinality
p5_hli has a high cardinality: 209 distinct values High cardinality
p5_hliye has a high cardinality: 212 distinct values High cardinality
p5_catolic has a high cardinality: 634 distinct values High cardinality
p5_ncatoli has a high cardinality: 213 distinct values High cardinality
p5_sinreli has a high cardinality: 270 distinct values High cardinality
pecoactiv has a high cardinality: 444 distinct values High cardinality
pecoinact has a high cardinality: 462 distinct values High cardinality
pocupada has a high cardinality: 451 distinct values High cardinality
pocusecp has a high cardinality: 323 distinct values High cardinality
pocusecs has a high cardinality: 240 distinct values High cardinality
pocusect has a high cardinality: 253 distinct values High cardinality
pocuningr has a high cardinality: 133 distinct values High cardinality
p_1sm has a high cardinality: 178 distinct values High cardinality
p1_2sm has a high cardinality: 325 distinct values High cardinality
p2_5sm has a high cardinality: 257 distinct values High cardinality
p6_10sm has a high cardinality: 128 distinct values High cardinality
p10_sm has a high cardinality: 97 distinct values High cardinality
pnotraba has a high cardinality: 90 distinct values High cardinality
p_32htra has a high cardinality: 217 distinct values High cardinality
p33_40htr has a high cardinality: 198 distinct values High cardinality
p41_48htr has a high cardinality: 304 distinct values High cardinality
p48_htr has a high cardinality: 241 distinct values High cardinality
vivparhab has a high cardinality: 376 distinct values High cardinality
ocuvivpar has a high cardinality: 684 distinct values High cardinality
pro_ovp has a high cardinality: 380 distinct values High cardinality
pro_ocvp has a high cardinality: 327 distinct values High cardinality
vp_pardes has a high cardinality: 94 distinct values High cardinality
vp_tecdes has a high cardinality: 163 distinct values High cardinality
vp_pisdes has a high cardinality: 335 distinct values High cardinality
vp_ccuart has a high cardinality: 198 distinct values High cardinality
vp2_5cuar has a high cardinality: 334 distinct values High cardinality
vp_2cuar has a high cardinality: 191 distinct values High cardinality
v_1cuarto has a high cardinality: 133 distinct values High cardinality
vp_cocgas has a high cardinality: 343 distinct values High cardinality
vp_coclen has a high cardinality: 177 distinct values High cardinality
vp_sersan has a high cardinality: 347 distinct values High cardinality
vp_aguent has a high cardinality: 350 distinct values High cardinality
vp_drenaj has a high cardinality: 289 distinct values High cardinality
vp_electr has a high cardinality: 364 distinct values High cardinality
vp_dreagu has a high cardinality: 283 distinct values High cardinality
vp_dreele has a high cardinality: 275 distinct values High cardinality
vp_aguele has a high cardinality: 355 distinct values High cardinality
vp_agdrel has a high cardinality: 273 distinct values High cardinality
vp_noade has a high cardinality: 87 distinct values High cardinality
vp_propia has a high cardinality: 350 distinct values High cardinality
vp_ppagad has a high cardinality: 340 distinct values High cardinality
vp_ppagan has a high cardinality: 111 distinct values High cardinality
vp_rentad has a high cardinality: 115 distinct values High cardinality
vp_cbiene has a high cardinality: 74 distinct values High cardinality
vp_sbiene has a high cardinality: 102 distinct values High cardinality
vp_radio has a high cardinality: 336 distinct values High cardinality
vp_tv has a high cardinality: 342 distinct values High cardinality
vp_video has a high cardinality: 192 distinct values High cardinality
vp_refri has a high cardinality: 324 distinct values High cardinality
vp_lavad has a high cardinality: 272 distinct values High cardinality
vp_telef has a high cardinality: 194 distinct values High cardinality
vp_boiler has a high cardinality: 230 distinct values High cardinality
vp_autom has a high cardinality: 258 distinct values High cardinality
tothog has a high cardinality: 377 distinct values High cardinality
hogjefm has a high cardinality: 359 distinct values High cardinality
hogjeff has a high cardinality: 187 distinct values High cardinality
pobhog has a high cardinality: 685 distinct values High cardinality
phogjefm has a high cardinality: 657 distinct values High cardinality
phogjeff has a high cardinality: 303 distinct values High cardinality
longitud is highly correlated with latitudHigh correlation
latitud is highly correlated with longitud and 1 other fieldsHigh correlation
altitud is highly correlated with latitudHigh correlation
pobtot is highly correlated with totvivhabHigh correlation
totvivhab is highly correlated with pobtotHigh correlation
longitud is highly correlated with latitudHigh correlation
latitud is highly correlated with longitudHigh correlation
pobtot is highly correlated with totvivhabHigh correlation
totvivhab is highly correlated with pobtotHigh correlation
pobtot is highly correlated with totvivhabHigh correlation
totvivhab is highly correlated with pobtotHigh correlation
Año is highly correlated with pcdisvis and 16 other fieldsHigh correlation
pcdisvis is highly correlated with Año and 14 other fieldsHigh correlation
pnotraba is highly correlated with Año and 14 other fieldsHigh correlation
vp_cocpet is highly correlated with Año and 14 other fieldsHigh correlation
nom_ent is highly correlated with Año and 16 other fieldsHigh correlation
p5_hliyne is highly correlated with Año and 14 other fieldsHigh correlation
vp_coccar is highly correlated with Año and 14 other fieldsHigh correlation
vp_cbiene is highly correlated with Año and 14 other fieldsHigh correlation
nom_mun is highly correlated with Año and 2 other fieldsHigh correlation
gradoesco is highly correlated with Año and 2 other fieldsHigh correlation
vp_pardes is highly correlated with Año and 14 other fieldsHigh correlation
pcdislen is highly correlated with Año and 14 other fieldsHigh correlation
pcdisaud is highly correlated with Año and 14 other fieldsHigh correlation
pcdismen is highly correlated with Año and 14 other fieldsHigh correlation
p5_naesc is highly correlated with Año and 14 other fieldsHigh correlation
vp_noade is highly correlated with Año and 14 other fieldsHigh correlation
entidad is highly correlated with Año and 16 other fieldsHigh correlation
p10_sm is highly correlated with Año and 14 other fieldsHigh correlation
mun is highly correlated with nom_mun and 4 other fieldsHigh correlation
nom_mun is highly correlated with mun and 19 other fieldsHigh correlation
loc is highly correlated with mun and 2 other fieldsHigh correlation
longitud is highly correlated with mun and 3 other fieldsHigh correlation
latitud is highly correlated with mun and 4 other fieldsHigh correlation
altitud is highly correlated with mun and 3 other fieldsHigh correlation
pobtot is highly correlated with nom_mun and 14 other fieldsHigh correlation
pcdisaud is highly correlated with nom_mun and 15 other fieldsHigh correlation
pcdisvis is highly correlated with nom_mun and 15 other fieldsHigh correlation
pcdismen is highly correlated with nom_mun and 15 other fieldsHigh correlation
pcdislen is highly correlated with nom_mun and 15 other fieldsHigh correlation
p5_naesc is highly correlated with nom_mun and 15 other fieldsHigh correlation
gradoesco is highly correlated with pcdisaud and 12 other fieldsHigh correlation
p5_hliyne is highly correlated with nom_mun and 15 other fieldsHigh correlation
p10_sm is highly correlated with nom_mun and 15 other fieldsHigh correlation
pnotraba is highly correlated with nom_mun and 15 other fieldsHigh correlation
totvivhab is highly correlated with nom_mun and 14 other fieldsHigh correlation
vp_pardes is highly correlated with nom_mun and 15 other fieldsHigh correlation
vp_coccar is highly correlated with nom_mun and 15 other fieldsHigh correlation
vp_cocpet is highly correlated with nom_mun and 15 other fieldsHigh correlation
vp_noade is highly correlated with nom_mun and 15 other fieldsHigh correlation
vp_cbiene is highly correlated with nom_mun and 15 other fieldsHigh correlation
longitud has 206 (2.5%) missing values Missing
latitud has 206 (2.5%) missing values Missing
altitud has 206 (2.5%) missing values Missing
pobtot is highly skewed (γ1 = 71.29947098) Skewed
totvivhab is highly skewed (γ1 = 71.04097373) Skewed

Reproduction

Analysis started2022-11-07 04:04:18.749755
Analysis finished2022-11-07 04:05:15.861671
Duration57.11 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

Año
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size495.5 KiB
2000
8316 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2000
2nd row2000
3rd row2000
4th row2000
5th row2000

Common Values

ValueCountFrequency (%)
20008316
100.0%

Length

2022-11-06T21:05:15.994647image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-06T21:05:16.147648image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
20008316
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

entidad
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size479.3 KiB
26
8316 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26
2nd row26
3rd row26
4th row26
5th row26

Common Values

ValueCountFrequency (%)
268316
100.0%

Length

2022-11-06T21:05:17.408369image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-06T21:05:17.504880image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
268316
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

nom_ent
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size511.8 KiB
Sonora
8316 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSonora
2nd rowSonora
3rd rowSonora
4th rowSonora
5th rowSonora

Common Values

ValueCountFrequency (%)
Sonora8316
100.0%

Length

2022-11-06T21:05:17.632879image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-06T21:05:17.740879image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
sonora8316
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mun
Real number (ℝ≥0)

HIGH CORRELATION

Distinct73
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.28451178
Minimum0
Maximum72
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size65.1 KiB
2022-11-06T21:05:17.908882image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q118
median30
Q345
95-th percentile69
Maximum72
Range72
Interquartile range (IQR)27

Descriptive statistics

Standard deviation18.83837272
Coefficient of variation (CV)0.5835111538
Kurtosis-0.6409398956
Mean32.28451178
Median Absolute Deviation (MAD)12
Skewness0.4503334264
Sum268478
Variance354.8842868
MonotonicityIncreasing
2022-11-06T21:05:18.348882image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301108
 
13.3%
18947
 
11.4%
17420
 
5.1%
29418
 
5.0%
42371
 
4.5%
55359
 
4.3%
3339
 
4.1%
26226
 
2.7%
33222
 
2.7%
12206
 
2.5%
Other values (63)3700
44.5%
ValueCountFrequency (%)
03
 
< 0.1%
18
 
0.1%
2162
1.9%
3339
4.1%
4172
2.1%
58
 
0.1%
6104
 
1.3%
710
 
0.1%
88
 
0.1%
921
 
0.3%
ValueCountFrequency (%)
72164
2.0%
71112
1.3%
7080
1.0%
6998
1.2%
6866
0.8%
6714
 
0.2%
6698
1.2%
6580
1.0%
6483
1.0%
636
 
0.1%

nom_mun
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct73
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size571.4 KiB
Hermosillo
1108 
Cajeme
947 
Caborca
 
420
Guaymas
 
418
Navojoa
 
371
Other values (68)
5052 

Length

Max length29
Median length7
Mean length9.104617605
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTotal de la entidad Sonora
2nd rowTotal de la entidad Sonora
3rd rowTotal de la entidad Sonora
4th rowAconchi
5th rowAconchi

Common Values

ValueCountFrequency (%)
Hermosillo1108
 
13.3%
Cajeme947
 
11.4%
Caborca420
 
5.1%
Guaymas418
 
5.0%
Navojoa371
 
4.5%
San Luis Río Colorado359
 
4.3%
Alamos339
 
4.1%
Etchojoa226
 
2.7%
Huatabampo222
 
2.7%
Bácum206
 
2.5%
Other values (63)3700
44.5%

Length

2022-11-06T21:05:18.623881image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hermosillo1108
 
9.8%
cajeme947
 
8.4%
san638
 
5.7%
río523
 
4.6%
caborca420
 
3.7%
guaymas418
 
3.7%
navojoa371
 
3.3%
luis359
 
3.2%
colorado359
 
3.2%
alamos339
 
3.0%
Other values (86)5804
51.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loc
Real number (ℝ≥0)

HIGH CORRELATION

Distinct2310
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean771.6065416
Minimum0
Maximum9999
Zeros73
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size65.1 KiB
2022-11-06T21:05:18.872915image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q1102
median301
Q3815
95-th percentile2988.25
Maximum9999
Range9999
Interquartile range (IQR)713

Descriptive statistics

Standard deviation1420.523009
Coefficient of variation (CV)1.840993995
Kurtosis25.99649427
Mean771.6065416
Median Absolute Deviation (MAD)248
Skewness4.629659545
Sum6416680
Variance2017885.62
MonotonicityNot monotonic
2022-11-06T21:05:19.176910image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
073
 
0.9%
999872
 
0.9%
172
 
0.9%
999961
 
0.7%
233
 
0.4%
2532
 
0.4%
830
 
0.4%
3728
 
0.3%
1728
 
0.3%
1128
 
0.3%
Other values (2300)7859
94.5%
ValueCountFrequency (%)
073
0.9%
172
0.9%
233
0.4%
328
 
0.3%
427
 
0.3%
526
 
0.3%
626
 
0.3%
726
 
0.3%
830
0.4%
928
 
0.3%
ValueCountFrequency (%)
999961
0.7%
999872
0.9%
36431
 
< 0.1%
36421
 
< 0.1%
36371
 
< 0.1%
36361
 
< 0.1%
36341
 
< 0.1%
36321
 
< 0.1%
36281
 
< 0.1%
36271
 
< 0.1%

nom_loc
Categorical

HIGH CARDINALITY

Distinct6155
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Memory size596.0 KiB
LOCALIDADES DE UNA VIVIENDA
 
72
TOTAL MUNICIPAL
 
72
LOCALIDADES DE DOS VIVIENDAS
 
61
LOCALIDAD SIN NOMBRE
 
51
SAN FRANCISCO
 
41
Other values (6150)
8019 

Length

Max length45
Median length13
Mean length15.67845118
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5451 ?
Unique (%)65.5%

Sample

1st rowTOTAL DE LA ENTIDAD
2nd rowLOCALIDADES DE UNA VIVIENDA
3rd rowLOCALIDADES DE DOS VIVIENDAS
4th rowTOTAL MUNICIPAL
5th rowACONCHI

Common Values

ValueCountFrequency (%)
LOCALIDADES DE UNA VIVIENDA72
 
0.9%
TOTAL MUNICIPAL72
 
0.9%
LOCALIDADES DE DOS VIVIENDAS61
 
0.7%
LOCALIDAD SIN NOMBRE51
 
0.6%
SAN FRANCISCO41
 
0.5%
RANCHITO, EL28
 
0.3%
SAN JOSE26
 
0.3%
SAN ANTONIO26
 
0.3%
SAN ISIDRO23
 
0.3%
ALAMO, EL22
 
0.3%
Other values (6145)7894
94.9%

Length

2022-11-06T21:05:19.439910image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
el1666
 
7.9%
la1223
 
5.8%
de778
 
3.7%
san663
 
3.1%
los539
 
2.6%
campo372
 
1.8%
las361
 
1.7%
santa335
 
1.6%
rancho260
 
1.2%
bloque187
 
0.9%
Other values (4434)14736
69.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

longitud
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5633
Distinct (%)69.5%
Missing206
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean1104229.814
Minimum1082903
Maximum1150230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.1 KiB
2022-11-06T21:05:19.692912image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1082903
5-th percentile1085753.35
Q11094453
median1101847
Q31111546.75
95-th percentile1130018.3
Maximum1150230
Range67327
Interquartile range (IQR)17093.75

Descriptive statistics

Standard deviation13336.77405
Coefficient of variation (CV)0.01207789708
Kurtosis1.892526009
Mean1104229.814
Median Absolute Deviation (MAD)8242.5
Skewness1.270273324
Sum8955303793
Variance177869542.1
MonotonicityNot monotonic
2022-11-06T21:05:19.943954image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
109560025
 
0.3%
109533016
 
0.2%
110005614
 
0.2%
110543013
 
0.2%
110032111
 
0.1%
10953259
 
0.1%
10951029
 
0.1%
10951009
 
0.1%
11007009
 
0.1%
10958258
 
0.1%
Other values (5623)7987
96.0%
(Missing)206
 
2.5%
ValueCountFrequency (%)
10829031
< 0.1%
10830041
< 0.1%
10830301
< 0.1%
10830531
< 0.1%
10831011
< 0.1%
10831121
< 0.1%
10831351
< 0.1%
10832181
< 0.1%
10832201
< 0.1%
10832251
< 0.1%
ValueCountFrequency (%)
11502301
< 0.1%
11501211
< 0.1%
11501181
< 0.1%
11501101
< 0.1%
11500561
< 0.1%
11500511
< 0.1%
11500272
< 0.1%
11500202
< 0.1%
11500182
< 0.1%
11500152
< 0.1%

latitud
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5992
Distinct (%)73.9%
Missing206
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean288262.5891
Minimum261926
Maximum322927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.1 KiB
2022-11-06T21:05:20.201973image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum261926
5-th percentile265405.8
Q1272854.25
median285249
Q3303354
95-th percentile314216.85
Maximum322927
Range61001
Interquartile range (IQR)30499.75

Descriptive statistics

Standard deviation16119.03875
Coefficient of variation (CV)0.0559179004
Kurtosis-1.036123712
Mean288262.5891
Median Absolute Deviation (MAD)13419
Skewness0.3235063014
Sum2337809598
Variance259823410.2
MonotonicityNot monotonic
2022-11-06T21:05:20.561971image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27190014
 
0.2%
27240011
 
0.1%
27311010
 
0.1%
27133010
 
0.1%
27243410
 
0.1%
2724299
 
0.1%
2723269
 
0.1%
2721108
 
0.1%
2710158
 
0.1%
2721178
 
0.1%
Other values (5982)8013
96.4%
(Missing)206
 
2.5%
ValueCountFrequency (%)
2619261
< 0.1%
2621591
< 0.1%
2622581
< 0.1%
2623261
< 0.1%
2624031
< 0.1%
2624151
< 0.1%
2624181
< 0.1%
2624211
< 0.1%
2624281
< 0.1%
2625241
< 0.1%
ValueCountFrequency (%)
3229271
< 0.1%
3229232
< 0.1%
3229031
< 0.1%
3229021
< 0.1%
3229001
< 0.1%
3228541
< 0.1%
3228531
< 0.1%
3228501
< 0.1%
3228491
< 0.1%
3228361
< 0.1%

altitud
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct264
Distinct (%)3.3%
Missing206
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean366.241307
Minimum0
Maximum2700
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size65.1 KiB
2022-11-06T21:05:20.774000image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q130
median180
Q3620
95-th percentile1240
Maximum2700
Range2700
Interquartile range (IQR)590

Descriptive statistics

Standard deviation422.2459432
Coefficient of variation (CV)1.152917312
Kurtosis0.683028371
Mean366.241307
Median Absolute Deviation (MAD)160
Skewness1.219753334
Sum2970217
Variance178291.6365
MonotonicityNot monotonic
2022-11-06T21:05:21.116999image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20702
 
8.4%
10612
 
7.4%
40429
 
5.2%
50347
 
4.2%
30308
 
3.7%
60228
 
2.7%
25164
 
2.0%
15122
 
1.5%
80119
 
1.4%
5118
 
1.4%
Other values (254)4961
59.7%
(Missing)206
 
2.5%
ValueCountFrequency (%)
01
 
< 0.1%
26
 
0.1%
35
 
0.1%
41
 
< 0.1%
5118
 
1.4%
61
 
< 0.1%
82
 
< 0.1%
10612
7.4%
1210
 
0.1%
141
 
< 0.1%
ValueCountFrequency (%)
27001
 
< 0.1%
22801
 
< 0.1%
22001
 
< 0.1%
21002
< 0.1%
20451
 
< 0.1%
20003
< 0.1%
19801
 
< 0.1%
19501
 
< 0.1%
19401
 
< 0.1%
18801
 
< 0.1%

pobtot
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct702
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean806.228355
Minimum1
Maximum2216969
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.1 KiB
2022-11-06T21:05:21.368060image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q314
95-th percentile385
Maximum2216969
Range2216968
Interquartile range (IQR)12

Descriptive statistics

Standard deviation26757.07741
Coefficient of variation (CV)33.18796374
Kurtosis5719.110813
Mean806.228355
Median Absolute Deviation (MAD)3
Skewness71.29947098
Sum6704595
Variance715941191.8
MonotonicityNot monotonic
2022-11-06T21:05:21.650013image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11232
14.8%
2980
 
11.8%
3805
 
9.7%
4767
 
9.2%
5675
 
8.1%
6487
 
5.9%
7310
 
3.7%
8244
 
2.9%
9194
 
2.3%
10170
 
2.0%
Other values (692)2452
29.5%
ValueCountFrequency (%)
11232
14.8%
2980
11.8%
3805
9.7%
4767
9.2%
5675
8.1%
6487
 
5.9%
7310
 
3.7%
8244
 
2.9%
9194
 
2.3%
10170
 
2.0%
ValueCountFrequency (%)
22169691
< 0.1%
6098291
< 0.1%
5459281
< 0.1%
3562901
< 0.1%
2507901
< 0.1%
1597871
< 0.1%
1568541
< 0.1%
1450061
< 0.1%
1406501
< 0.1%
1303291
< 0.1%

pmascul
Categorical

HIGH CARDINALITY

Distinct531
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size473.7 KiB
*
5795 
6
 
133
8
 
132
7
 
119
5
 
105
Other values (526)
2032 

Length

Max length7
Median length1
Mean length1.314093314
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique311 ?
Unique (%)3.7%

Sample

1st row1110590
2nd row10718
3rd row5314
4th row1268
5th row866

Common Values

ValueCountFrequency (%)
*5795
69.7%
6133
 
1.6%
8132
 
1.6%
7119
 
1.4%
5105
 
1.3%
988
 
1.1%
481
 
1.0%
1271
 
0.9%
1067
 
0.8%
1158
 
0.7%
Other values (521)1667
 
20.0%

Length

2022-11-06T21:05:21.953061image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
6133
 
1.6%
8132
 
1.6%
7119
 
1.4%
5105
 
1.3%
988
 
1.1%
481
 
1.0%
1271
 
0.9%
1067
 
0.8%
1158
 
0.7%
Other values (521)1667
 
20.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pfemeni
Categorical

HIGH CARDINALITY

Distinct511
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size473.5 KiB
*
5795 
6
 
139
4
 
116
7
 
105
8
 
104
Other values (506)
2057 

Length

Max length7
Median length1
Mean length1.291726792
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique307 ?
Unique (%)3.7%

Sample

1st row1106379
2nd row7215
3rd row3597
4th row1152
5th row781

Common Values

ValueCountFrequency (%)
*5795
69.7%
6139
 
1.7%
4116
 
1.4%
7105
 
1.3%
8104
 
1.3%
598
 
1.2%
391
 
1.1%
985
 
1.0%
1083
 
1.0%
273
 
0.9%
Other values (501)1627
 
19.6%

Length

2022-11-06T21:05:22.315052image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
6139
 
1.7%
4116
 
1.4%
7105
 
1.3%
8104
 
1.3%
598
 
1.2%
391
 
1.1%
985
 
1.0%
1083
 
1.0%
273
 
0.9%
Other values (501)1627
 
19.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob0_4
Categorical

HIGH CARDINALITY

Distinct275
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size472.4 KiB
*
5795 
0
 
301
2
 
295
1
 
279
3
 
185
Other values (270)
1461 

Length

Max length6
Median length1
Mean length1.151034151
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)1.9%

Sample

1st row244619
2nd row1843
3rd row894
4th row238
5th row163

Common Values

ValueCountFrequency (%)
*5795
69.7%
0301
 
3.6%
2295
 
3.5%
1279
 
3.4%
3185
 
2.2%
4140
 
1.7%
5106
 
1.3%
682
 
1.0%
768
 
0.8%
953
 
0.6%
Other values (265)1012
 
12.2%

Length

2022-11-06T21:05:22.550065image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0301
 
3.6%
2295
 
3.5%
1279
 
3.4%
3185
 
2.2%
4140
 
1.7%
5106
 
1.3%
682
 
1.0%
768
 
0.8%
953
 
0.6%
Other values (265)1012
 
12.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_mas
Categorical

HIGH CARDINALITY

Distinct646
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size474.4 KiB
*
5795 
10
 
89
11
 
81
9
 
76
12
 
69
Other values (641)
2206 

Length

Max length7
Median length1
Mean length1.394901395
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique381 ?
Unique (%)4.6%

Sample

1st row1956617
2nd row15970
3rd row7792
4th row2163
5th row1470

Common Values

ValueCountFrequency (%)
*5795
69.7%
1089
 
1.1%
1181
 
1.0%
976
 
0.9%
1269
 
0.8%
1365
 
0.8%
1663
 
0.8%
762
 
0.7%
1857
 
0.7%
857
 
0.7%
Other values (636)1902
 
22.9%

Length

2022-11-06T21:05:22.771103image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1089
 
1.1%
1181
 
1.0%
976
 
0.9%
1269
 
0.8%
1365
 
0.8%
1663
 
0.8%
762
 
0.7%
1857
 
0.7%
857
 
0.7%
Other values (636)1902
 
22.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob6_14
Categorical

HIGH CARDINALITY

Distinct350
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size472.7 KiB
*
5795 
0
 
263
2
 
186
3
 
179
1
 
173
Other values (345)
1720 

Length

Max length6
Median length1
Mean length1.191919192
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)2.4%

Sample

1st row424847
2nd row2724
3rd row1108
4th row438
5th row292

Common Values

ValueCountFrequency (%)
*5795
69.7%
0263
 
3.2%
2186
 
2.2%
3179
 
2.2%
1173
 
2.1%
4147
 
1.8%
5126
 
1.5%
694
 
1.1%
778
 
0.9%
866
 
0.8%
Other values (340)1209
 
14.5%

Length

2022-11-06T21:05:22.986215image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0263
 
3.2%
2186
 
2.2%
3179
 
2.2%
1173
 
2.1%
4147
 
1.8%
5126
 
1.5%
694
 
1.1%
778
 
0.9%
866
 
0.8%
Other values (340)1209
 
14.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob12_
Categorical

HIGH CARDINALITY

Distinct605
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size474.1 KiB
*
5795 
9
 
116
7
 
98
10
 
90
6
 
83
Other values (600)
2134 

Length

Max length7
Median length1
Mean length1.363636364
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique358 ?
Unique (%)4.3%

Sample

1st row1617117
2nd row13802
3rd row6875
4th row1821
5th row1241

Common Values

ValueCountFrequency (%)
*5795
69.7%
9116
 
1.4%
798
 
1.2%
1090
 
1.1%
683
 
1.0%
883
 
1.0%
1174
 
0.9%
1364
 
0.8%
1258
 
0.7%
1554
 
0.6%
Other values (595)1801
 
21.7%

Length

2022-11-06T21:05:23.231293image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
9116
 
1.4%
798
 
1.2%
1090
 
1.1%
683
 
1.0%
883
 
1.0%
1174
 
0.9%
1364
 
0.8%
1258
 
0.7%
1554
 
0.6%
Other values (595)1801
 
21.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob15_
Categorical

HIGH CARDINALITY

Distinct584
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size474.0 KiB
*
5795 
9
 
119
7
 
109
10
 
102
6
 
100
Other values (579)
2091 

Length

Max length7
Median length1
Mean length1.351250601
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)4.0%

Sample

1st row1482068
2nd row12906
3rd row6527
4th row1679
5th row1146

Common Values

ValueCountFrequency (%)
*5795
69.7%
9119
 
1.4%
7109
 
1.3%
10102
 
1.2%
6100
 
1.2%
894
 
1.1%
1171
 
0.9%
567
 
0.8%
1462
 
0.7%
1258
 
0.7%
Other values (574)1739
 
20.9%

Length

2022-11-06T21:05:23.491292image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
9119
 
1.4%
7109
 
1.3%
10102
 
1.2%
6100
 
1.2%
894
 
1.1%
1171
 
0.9%
567
 
0.8%
1462
 
0.7%
1258
 
0.7%
Other values (574)1739
 
20.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob15_17
Categorical

HIGH CARDINALITY

Distinct218
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
0
 
571
1
 
415
2
 
269
3
 
165
Other values (213)
1101 

Length

Max length6
Median length1
Mean length1.112794613
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)1.5%

Sample

1st row131769
2nd row999
3rd row390
4th row144
5th row100

Common Values

ValueCountFrequency (%)
*5795
69.7%
0571
 
6.9%
1415
 
5.0%
2269
 
3.2%
3165
 
2.0%
4104
 
1.3%
587
 
1.0%
746
 
0.6%
645
 
0.5%
1138
 
0.5%
Other values (208)781
 
9.4%

Length

2022-11-06T21:05:23.711298image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0571
 
6.9%
1415
 
5.0%
2269
 
3.2%
3165
 
2.0%
4104
 
1.3%
587
 
1.0%
746
 
0.6%
645
 
0.5%
1138
 
0.5%
Other values (208)781
 
9.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob15_24
Categorical

HIGH CARDINALITY

Distinct355
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size472.7 KiB
*
5795 
2
 
204
1
 
202
3
 
199
0
 
177
Other values (350)
1739 

Length

Max length6
Median length1
Mean length1.193121693
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)2.5%

Sample

1st row429168
2nd row3445
3rd row1733
4th row441
5th row302

Common Values

ValueCountFrequency (%)
*5795
69.7%
2204
 
2.5%
1202
 
2.4%
3199
 
2.4%
0177
 
2.1%
4163
 
2.0%
5110
 
1.3%
690
 
1.1%
781
 
1.0%
962
 
0.7%
Other values (345)1233
 
14.8%

Length

2022-11-06T21:05:23.940297image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
2204
 
2.5%
1202
 
2.4%
3199
 
2.4%
0177
 
2.1%
4163
 
2.0%
5110
 
1.3%
690
 
1.1%
781
 
1.0%
962
 
0.7%
Other values (345)1233
 
14.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pobf15_49
Categorical

HIGH CARDINALITY

Distinct384
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size472.8 KiB
*
5795 
3
 
228
4
 
198
2
 
180
5
 
159
Other values (379)
1756 

Length

Max length6
Median length1
Mean length1.208273208
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)2.8%

Sample

1st row594782
2nd row3594
3rd row1921
4th row597
5th row406

Common Values

ValueCountFrequency (%)
*5795
69.7%
3228
 
2.7%
4198
 
2.4%
2180
 
2.2%
5159
 
1.9%
1132
 
1.6%
6110
 
1.3%
882
 
1.0%
080
 
1.0%
772
 
0.9%
Other values (374)1280
 
15.4%

Length

2022-11-06T21:05:24.197399image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3228
 
2.7%
4198
 
2.4%
2180
 
2.2%
5159
 
1.9%
1132
 
1.6%
6110
 
1.3%
882
 
1.0%
080
 
1.0%
772
 
0.9%
Other values (374)1280
 
15.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob18_
Categorical

HIGH CARDINALITY

Distinct568
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size473.9 KiB
*
5795 
6
 
125
8
 
116
7
 
114
9
 
106
Other values (563)
2060 

Length

Max length7
Median length1
Mean length1.335497835
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338 ?
Unique (%)4.1%

Sample

1st row1350299
2nd row11907
3rd row6137
4th row1535
5th row1046

Common Values

ValueCountFrequency (%)
*5795
69.7%
6125
 
1.5%
8116
 
1.4%
7114
 
1.4%
9106
 
1.3%
10102
 
1.2%
589
 
1.1%
1172
 
0.9%
1362
 
0.7%
1257
 
0.7%
Other values (558)1678
 
20.2%

Length

2022-11-06T21:05:24.433416image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
6125
 
1.5%
8116
 
1.4%
7114
 
1.4%
9106
 
1.3%
10102
 
1.2%
589
 
1.1%
1172
 
0.9%
1362
 
0.7%
1257
 
0.7%
Other values (558)1678
 
20.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pmasc18_
Categorical

HIGH CARDINALITY

Distinct439
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size473.2 KiB
*
5795 
5
 
211
3
 
200
4
 
200
6
 
122
Other values (434)
1788 

Length

Max length6
Median length1
Mean length1.248917749
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)3.0%

Sample

1st row669847
2nd row7498
3rd row3854
4th row795
5th row543

Common Values

ValueCountFrequency (%)
*5795
69.7%
5211
 
2.5%
3200
 
2.4%
4200
 
2.4%
6122
 
1.5%
7109
 
1.3%
893
 
1.1%
980
 
1.0%
1063
 
0.8%
1157
 
0.7%
Other values (429)1386
 
16.7%

Length

2022-11-06T21:05:24.688612image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
5211
 
2.5%
3200
 
2.4%
4200
 
2.4%
6122
 
1.5%
7109
 
1.3%
893
 
1.1%
980
 
1.0%
1063
 
0.8%
1157
 
0.7%
Other values (429)1386
 
16.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pfemen18_
Categorical

HIGH CARDINALITY

Distinct412
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size473.0 KiB
*
5795 
3
 
219
4
 
207
5
 
162
2
 
151
Other values (407)
1782 

Length

Max length6
Median length1
Mean length1.224266474
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)2.8%

Sample

1st row680452
2nd row4409
3rd row2283
4th row740
5th row503

Common Values

ValueCountFrequency (%)
*5795
69.7%
3219
 
2.6%
4207
 
2.5%
5162
 
1.9%
2151
 
1.8%
6123
 
1.5%
799
 
1.2%
191
 
1.1%
889
 
1.1%
953
 
0.6%
Other values (402)1327
 
16.0%

Length

2022-11-06T21:05:24.905686image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3219
 
2.6%
4207
 
2.5%
5162
 
1.9%
2151
 
1.8%
6123
 
1.5%
799
 
1.2%
191
 
1.1%
889
 
1.1%
953
 
0.6%
Other values (402)1327
 
16.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

psderss
Categorical

HIGH CARDINALITY

Distinct586
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size473.8 KiB
*
5795 
0
 
88
3
 
87
2
 
83
4
 
81
Other values (581)
2182 

Length

Max length6
Median length1
Mean length1.324194324
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)4.2%

Sample

1st row925481
2nd row9918
3rd row5027
4th row1539
5th row974

Common Values

ValueCountFrequency (%)
*5795
69.7%
088
 
1.1%
387
 
1.0%
283
 
1.0%
481
 
1.0%
775
 
0.9%
874
 
0.9%
572
 
0.9%
670
 
0.8%
167
 
0.8%
Other values (576)1824
 
21.9%

Length

2022-11-06T21:05:25.125685image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
088
 
1.1%
387
 
1.0%
283
 
1.0%
481
 
1.0%
775
 
0.9%
874
 
0.9%
572
 
0.9%
670
 
0.8%
167
 
0.8%
Other values (576)1824
 
21.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcderss
Categorical

HIGH CARDINALITY

Distinct440
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size473.2 KiB
*
5795 
0
 
259
2
 
110
1
 
100
5
 
93
Other values (435)
1959 

Length

Max length7
Median length1
Mean length1.257215007
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)3.0%

Sample

1st row1250610
2nd row7673
3rd row3596
4th row843
5th row652

Common Values

ValueCountFrequency (%)
*5795
69.7%
0259
 
3.1%
2110
 
1.3%
1100
 
1.2%
593
 
1.1%
692
 
1.1%
785
 
1.0%
481
 
1.0%
369
 
0.8%
969
 
0.8%
Other values (430)1563
 
18.8%

Length

2022-11-06T21:05:25.314680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0259
 
3.1%
2110
 
1.3%
1100
 
1.2%
593
 
1.1%
692
 
1.1%
785
 
1.0%
481
 
1.0%
369
 
0.8%
969
 
0.8%
Other values (430)1563
 
18.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pderimss
Categorical

HIGH CARDINALITY

Distinct403
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size473.1 KiB
*
5795 
0
 
303
2
 
113
1
 
110
4
 
93
Other values (398)
1902 

Length

Max length7
Median length1
Mean length1.238455988
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique244 ?
Unique (%)2.9%

Sample

1st row1015636
2nd row7330
3rd row3416
4th row601
5th row448

Common Values

ValueCountFrequency (%)
*5795
69.7%
0303
 
3.6%
2113
 
1.4%
1110
 
1.3%
493
 
1.1%
589
 
1.1%
389
 
1.1%
683
 
1.0%
780
 
1.0%
977
 
0.9%
Other values (393)1484
 
17.8%

Length

2022-11-06T21:05:25.487679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0303
 
3.6%
2113
 
1.4%
1110
 
1.3%
493
 
1.1%
589
 
1.1%
389
 
1.1%
683
 
1.0%
780
 
1.0%
977
 
0.9%
Other values (393)1484
 
17.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pderiste
Categorical

HIGH CARDINALITY

Distinct200
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1518 
1
 
117
2
 
103
4
 
71
Other values (195)
712 

Length

Max length6
Median length1
Mean length1.077441077
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)1.4%

Sample

1st row144635
2nd row199
3rd row102
4th row109
5th row89

Common Values

ValueCountFrequency (%)
*5795
69.7%
01518
 
18.3%
1117
 
1.4%
2103
 
1.2%
471
 
0.9%
371
 
0.9%
549
 
0.6%
641
 
0.5%
732
 
0.4%
827
 
0.3%
Other values (190)492
 
5.9%

Length

2022-11-06T21:05:25.737682image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01518
 
18.3%
1117
 
1.4%
2103
 
1.2%
471
 
0.9%
371
 
0.9%
549
 
0.6%
641
 
0.5%
732
 
0.4%
827
 
0.3%
Other values (190)492
 
5.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacent
Categorical

HIGH CARDINALITY

Distinct646
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size474.2 KiB
*
5795 
11
 
84
13
 
79
10
 
70
14
 
68
Other values (641)
2220 

Length

Max length7
Median length1
Mean length1.37987013
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique393 ?
Unique (%)4.7%

Sample

1st row1827379
2nd row13861
3rd row6788
4th row2377
5th row1615

Common Values

ValueCountFrequency (%)
*5795
69.7%
1184
 
1.0%
1379
 
0.9%
1070
 
0.8%
1468
 
0.8%
1265
 
0.8%
864
 
0.8%
663
 
0.8%
761
 
0.7%
560
 
0.7%
Other values (636)1907
 
22.9%

Length

2022-11-06T21:05:25.970472image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1184
 
1.0%
1379
 
0.9%
1070
 
0.8%
1468
 
0.8%
1265
 
0.8%
864
 
0.8%
663
 
0.8%
761
 
0.7%
560
 
0.7%
Other values (636)1907
 
22.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacoent
Categorical

HIGH CARDINALITY

Distinct272
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size472.2 KiB
*
5795 
0
585 
1
 
266
2
 
182
3
 
151
Other values (267)
1337 

Length

Max length6
Median length1
Mean length1.134439634
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)2.0%

Sample

1st row372842
2nd row3907
3rd row1904
4th row21
5th row17

Common Values

ValueCountFrequency (%)
*5795
69.7%
0585
 
7.0%
1266
 
3.2%
2182
 
2.2%
3151
 
1.8%
4122
 
1.5%
5116
 
1.4%
693
 
1.1%
769
 
0.8%
957
 
0.7%
Other values (262)880
 
10.6%

Length

2022-11-06T21:05:26.182498image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0585
 
7.0%
1266
 
3.2%
2182
 
2.2%
3151
 
1.8%
4122
 
1.5%
5116
 
1.4%
693
 
1.1%
769
 
0.8%
957
 
0.7%
Other values (262)880
 
10.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_res95
Categorical

HIGH CARDINALITY

Distinct663
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size474.3 KiB
*
5795 
10
 
89
11
 
83
9
 
78
13
 
74
Other values (658)
2197 

Length

Max length7
Median length1
Mean length1.384680135
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)5.1%

Sample

1st row1862929
2nd row13959
3rd row6919
4th row2135
5th row1449

Common Values

ValueCountFrequency (%)
*5795
69.7%
1089
 
1.1%
1183
 
1.0%
978
 
0.9%
1374
 
0.9%
1264
 
0.8%
764
 
0.8%
860
 
0.7%
1457
 
0.7%
656
 
0.7%
Other values (653)1896
 
22.8%

Length

2022-11-06T21:05:26.399503image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1089
 
1.1%
1183
 
1.0%
978
 
0.9%
1374
 
0.9%
1264
 
0.8%
764
 
0.8%
860
 
0.7%
1457
 
0.7%
1656
 
0.7%
Other values (653)1896
 
22.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_reso95
Categorical

HIGH CARDINALITY

Distinct167
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size471.7 KiB
*
5795 
0
1441 
1
 
229
2
 
138
3
 
84
Other values (162)
629 

Length

Max length5
Median length1
Mean length1.062650313
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)1.3%

Sample

1st row86120
2nd row1904
3rd row848
4th row24
5th row17

Common Values

ValueCountFrequency (%)
*5795
69.7%
01441
 
17.3%
1229
 
2.8%
2138
 
1.7%
384
 
1.0%
477
 
0.9%
554
 
0.6%
642
 
0.5%
835
 
0.4%
733
 
0.4%
Other values (157)388
 
4.7%

Length

2022-11-06T21:05:26.600559image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01441
 
17.3%
1229
 
2.8%
2138
 
1.7%
384
 
1.0%
477
 
0.9%
554
 
0.6%
642
 
0.5%
835
 
0.4%
733
 
0.4%
Other values (157)388
 
4.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcondisc
Categorical

HIGH CARDINALITY

Distinct145
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size471.7 KiB
*
5795 
0
1089 
1
 
385
2
 
203
3
 
128
Other values (140)
716 

Length

Max length5
Median length1
Mean length1.063131313
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.0%

Sample

1st row42022
2nd row445
3rd row193
4th row67
5th row47

Common Values

ValueCountFrequency (%)
*5795
69.7%
01089
 
13.1%
1385
 
4.6%
2203
 
2.4%
3128
 
1.5%
484
 
1.0%
560
 
0.7%
658
 
0.7%
737
 
0.4%
835
 
0.4%
Other values (135)442
 
5.3%

Length

2022-11-06T21:05:26.787174image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01089
 
13.1%
1385
 
4.6%
2203
 
2.4%
3128
 
1.5%
484
 
1.0%
560
 
0.7%
658
 
0.7%
737
 
0.4%
835
 
0.4%
Other values (135)442
 
5.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcdismot
Categorical

HIGH CARDINALITY

Distinct109
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size471.5 KiB
*
5795 
0
1440 
1
 
356
2
 
184
3
 
79
Other values (104)
 
462

Length

Max length5
Median length1
Mean length1.037397787
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)0.8%

Sample

1st row21046
2nd row188
3rd row81
4th row30
5th row21

Common Values

ValueCountFrequency (%)
*5795
69.7%
01440
 
17.3%
1356
 
4.3%
2184
 
2.2%
379
 
0.9%
467
 
0.8%
555
 
0.7%
646
 
0.6%
822
 
0.3%
1022
 
0.3%
Other values (99)250
 
3.0%

Length

2022-11-06T21:05:26.981144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01440
 
17.3%
1356
 
4.3%
2184
 
2.2%
379
 
0.9%
467
 
0.8%
555
 
0.7%
646
 
0.6%
822
 
0.3%
1022
 
0.3%
Other values (99)250
 
3.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcdisaud
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct68
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size471.3 KiB
*
5795 
0
1775 
1
 
318
2
 
114
3
 
66
Other values (63)
 
248

Length

Max length4
Median length1
Mean length1.02020202
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.4%

Sample

1st row5824
2nd row75
3rd row32
4th row8
5th row6

Common Values

ValueCountFrequency (%)
*5795
69.7%
01775
 
21.3%
1318
 
3.8%
2114
 
1.4%
366
 
0.8%
437
 
0.4%
625
 
0.3%
525
 
0.3%
N/D15
 
0.2%
713
 
0.2%
Other values (58)133
 
1.6%

Length

2022-11-06T21:05:27.164142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01775
 
21.3%
1318
 
3.8%
2114
 
1.4%
366
 
0.8%
437
 
0.4%
525
 
0.3%
625
 
0.3%
n/d15
 
0.2%
713
 
0.2%
Other values (58)133
 
1.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcdisvis
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct88
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
1659 
1
 
322
2
 
133
3
 
69
Other values (83)
 
338

Length

Max length4
Median length1
Mean length1.026455026
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.6%

Sample

1st row9099
2nd row127
3rd row64
4th row12
5th row12

Common Values

ValueCountFrequency (%)
*5795
69.7%
01659
 
19.9%
1322
 
3.9%
2133
 
1.6%
369
 
0.8%
553
 
0.6%
450
 
0.6%
628
 
0.3%
N/D15
 
0.2%
715
 
0.2%
Other values (78)177
 
2.1%

Length

2022-11-06T21:05:27.419141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01659
 
19.9%
1322
 
3.9%
2133
 
1.6%
369
 
0.8%
553
 
0.6%
450
 
0.6%
628
 
0.3%
n/d15
 
0.2%
715
 
0.2%
Other values (78)177
 
2.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcdismen
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct75
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size471.3 KiB
*
5795 
0
1780 
1
 
316
2
 
111
3
 
70
Other values (70)
 
244

Length

Max length4
Median length1
Mean length1.020923521
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)0.6%

Sample

1st row7311
2nd row69
3rd row25
4th row19
5th row10

Common Values

ValueCountFrequency (%)
*5795
69.7%
01780
 
21.4%
1316
 
3.8%
2111
 
1.3%
370
 
0.8%
431
 
0.4%
529
 
0.3%
618
 
0.2%
715
 
0.2%
N/D15
 
0.2%
Other values (65)136
 
1.6%

Length

2022-11-06T21:05:27.683142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01780
 
21.4%
1316
 
3.8%
2111
 
1.3%
370
 
0.8%
431
 
0.4%
529
 
0.3%
618
 
0.2%
n/d15
 
0.2%
715
 
0.2%
Other values (65)136
 
1.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcdislen
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct49
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size471.2 KiB
*
5795 
0
2098 
1
 
213
2
 
71
4
 
23
Other values (44)
 
116

Length

Max length4
Median length1
Mean length1.010582011
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)0.4%

Sample

1st row1737
2nd row18
3rd row10
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5795
69.7%
02098
 
25.2%
1213
 
2.6%
271
 
0.9%
423
 
0.3%
322
 
0.3%
N/D15
 
0.2%
510
 
0.1%
68
 
0.1%
87
 
0.1%
Other values (39)54
 
0.6%

Length

2022-11-06T21:05:28.065141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
02098
 
25.2%
1213
 
2.6%
271
 
0.9%
423
 
0.3%
322
 
0.3%
n/d15
 
0.2%
510
 
0.1%
68
 
0.1%
117
 
0.1%
Other values (39)54
 
0.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

psindisc
Categorical

HIGH CARDINALITY

Distinct681
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size474.5 KiB
*
5795 
12
 
79
13
 
72
11
 
67
9
 
63
Other values (676)
2240 

Length

Max length7
Median length1
Mean length1.407888408
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique413 ?
Unique (%)5.0%

Sample

1st row2151210
2nd row17257
3rd row8431
4th row2313
5th row1572

Common Values

ValueCountFrequency (%)
*5795
69.7%
1279
 
0.9%
1372
 
0.9%
1167
 
0.8%
963
 
0.8%
1558
 
0.7%
1655
 
0.7%
1055
 
0.7%
851
 
0.6%
1450
 
0.6%
Other values (671)1971
 
23.7%

Length

2022-11-06T21:05:28.306144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1279
 
0.9%
1372
 
0.9%
1167
 
0.8%
963
 
0.8%
1558
 
0.7%
1655
 
0.7%
1055
 
0.7%
851
 
0.6%
1450
 
0.6%
Other values (671)1971
 
23.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6_14slee
Categorical

HIGH CARDINALITY

Distinct336
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
0
 
334
2
 
225
1
 
191
3
 
190
Other values (331)
1581 

Length

Max length6
Median length1
Mean length1.175084175
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)2.4%

Sample

1st row371711
2nd row2052
3rd row840
4th row395
5th row268

Common Values

ValueCountFrequency (%)
*5795
69.7%
0334
 
4.0%
2225
 
2.7%
1191
 
2.3%
3190
 
2.3%
4165
 
2.0%
5111
 
1.3%
677
 
0.9%
762
 
0.7%
855
 
0.7%
Other values (326)1111
 
13.4%

Length

2022-11-06T21:05:28.496147image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0334
 
4.0%
2225
 
2.7%
1191
 
2.3%
3190
 
2.3%
4165
 
2.0%
5111
 
1.3%
677
 
0.9%
762
 
0.7%
855
 
0.7%
Other values (326)1111
 
13.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6_14nlee
Categorical

HIGH CARDINALITY

Distinct154
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
858 
1
 
408
2
 
226
3
 
133
Other values (149)
896 

Length

Max length5
Median length1
Mean length1.075998076
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)1.0%

Sample

1st row51283
2nd row639
3rd row258
4th row42
5th row23

Common Values

ValueCountFrequency (%)
*5795
69.7%
0858
 
10.3%
1408
 
4.9%
2226
 
2.7%
3133
 
1.6%
4109
 
1.3%
582
 
1.0%
858
 
0.7%
753
 
0.6%
647
 
0.6%
Other values (144)547
 
6.6%

Length

2022-11-06T21:05:28.673141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0858
 
10.3%
1408
 
4.9%
2226
 
2.7%
3133
 
1.6%
4109
 
1.3%
582
 
1.0%
858
 
0.7%
753
 
0.6%
647
 
0.6%
Other values (144)547
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_alfab
Categorical

HIGH CARDINALITY

Distinct561
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size473.8 KiB
*
5795 
7
 
121
8
 
115
9
 
105
6
 
96
Other values (556)
2084 

Length

Max length7
Median length1
Mean length1.329485329
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)3.9%

Sample

1st row1415320
2nd row11158
3rd row5772
4th row1591
5th row1092

Common Values

ValueCountFrequency (%)
*5795
69.7%
7121
 
1.5%
8115
 
1.4%
9105
 
1.3%
696
 
1.2%
595
 
1.1%
1089
 
1.1%
1175
 
0.9%
470
 
0.8%
1467
 
0.8%
Other values (551)1688
 
20.3%

Length

2022-11-06T21:05:28.856150image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
7121
 
1.5%
8115
 
1.4%
9105
 
1.3%
696
 
1.2%
595
 
1.1%
1089
 
1.1%
1175
 
0.9%
470
 
0.8%
1467
 
0.8%
Other values (551)1688
 
20.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_analf
Categorical

HIGH CARDINALITY

Distinct200
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
0
 
463
1
 
367
2
 
268
3
 
163
Other values (195)
1260 

Length

Max length5
Median length1
Mean length1.116642617
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)1.4%

Sample

1st row65066
2nd row1710
3rd row746
4th row86
5th row52

Common Values

ValueCountFrequency (%)
*5795
69.7%
0463
 
5.6%
1367
 
4.4%
2268
 
3.2%
3163
 
2.0%
4131
 
1.6%
581
 
1.0%
675
 
0.9%
760
 
0.7%
853
 
0.6%
Other values (190)860
 
10.3%

Length

2022-11-06T21:05:29.067143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0463
 
5.6%
1367
 
4.4%
2268
 
3.2%
3163
 
2.0%
4131
 
1.6%
581
 
1.0%
675
 
0.9%
760
 
0.7%
853
 
0.6%
Other values (190)860
 
10.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_asiesc
Categorical

HIGH CARDINALITY

Distinct116
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size471.5 KiB
*
5795 
0
1443 
1
 
291
2
 
127
3
 
77
Other values (111)
583 

Length

Max length5
Median length1
Mean length1.047138047
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)0.8%

Sample

1st row30616
2nd row104
3rd row56
4th row40
5th row29

Common Values

ValueCountFrequency (%)
*5795
69.7%
01443
 
17.4%
1291
 
3.5%
2127
 
1.5%
377
 
0.9%
575
 
0.9%
464
 
0.8%
643
 
0.5%
743
 
0.5%
829
 
0.3%
Other values (106)329
 
4.0%

Length

2022-11-06T21:05:29.335143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01443
 
17.4%
1291
 
3.5%
2127
 
1.5%
377
 
0.9%
575
 
0.9%
464
 
0.8%
643
 
0.5%
743
 
0.5%
829
 
0.3%
Other values (106)329
 
4.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_naesc
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct98
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
1433 
1
 
484
2
 
184
3
 
98
Other values (93)
 
322

Length

Max length5
Median length1
Mean length1.027537278
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)0.8%

Sample

1st row16137
2nd row218
3rd row92
4th row4
5th row1

Common Values

ValueCountFrequency (%)
*5795
69.7%
01433
 
17.2%
1484
 
5.8%
2184
 
2.2%
398
 
1.2%
443
 
0.5%
535
 
0.4%
627
 
0.3%
719
 
0.2%
818
 
0.2%
Other values (88)180
 
2.2%

Length

2022-11-06T21:05:29.541141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01433
 
17.2%
1484
 
5.8%
2184
 
2.2%
398
 
1.2%
443
 
0.5%
535
 
0.4%
627
 
0.3%
719
 
0.2%
818
 
0.2%
Other values (88)180
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6_14aesc
Categorical

HIGH CARDINALITY

Distinct349
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
0
 
356
2
 
201
1
 
195
3
 
182
Other values (344)
1587 

Length

Max length6
Median length1
Mean length1.17965368
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)2.5%

Sample

1st row398474
2nd row2025
3rd row881
4th row403
5th row273

Common Values

ValueCountFrequency (%)
*5795
69.7%
0356
 
4.3%
2201
 
2.4%
1195
 
2.3%
3182
 
2.2%
4143
 
1.7%
5112
 
1.3%
683
 
1.0%
768
 
0.8%
865
 
0.8%
Other values (339)1116
 
13.4%

Length

2022-11-06T21:05:29.738141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0356
 
4.3%
2201
 
2.4%
1195
 
2.3%
3182
 
2.2%
4143
 
1.7%
5112
 
1.3%
683
 
1.0%
768
 
0.8%
865
 
0.8%
Other values (339)1116
 
13.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6_14naesc
Categorical

HIGH CARDINALITY

Distinct125
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size471.5 KiB
*
5795 
0
1041 
1
 
418
2
 
268
3
 
150
Other values (120)
644 

Length

Max length5
Median length1
Mean length1.046657047
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)0.9%

Sample

1st row24191
2nd row657
3rd row216
4th row32
5th row17

Common Values

ValueCountFrequency (%)
*5795
69.7%
01041
 
12.5%
1418
 
5.0%
2268
 
3.2%
3150
 
1.8%
4111
 
1.3%
568
 
0.8%
653
 
0.6%
747
 
0.6%
836
 
0.4%
Other values (115)329
 
4.0%

Length

2022-11-06T21:05:29.988143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01041
 
12.5%
1418
 
5.0%
2268
 
3.2%
3150
 
1.8%
4111
 
1.3%
568
 
0.8%
653
 
0.6%
747
 
0.6%
836
 
0.4%
Other values (115)329
 
4.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_17aesc
Categorical

HIGH CARDINALITY

Distinct168
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size471.7 KiB
*
5795 
0
1146 
1
 
364
2
 
162
3
 
108
Other values (163)
741 

Length

Max length5
Median length1
Mean length1.072631073
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)1.2%

Sample

1st row82200
2nd row345
3rd row132
4th row75
5th row55

Common Values

ValueCountFrequency (%)
*5795
69.7%
01146
 
13.8%
1364
 
4.4%
2162
 
1.9%
3108
 
1.3%
472
 
0.9%
558
 
0.7%
746
 
0.6%
639
 
0.5%
833
 
0.4%
Other values (158)493
 
5.9%

Length

2022-11-06T21:05:30.228141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01146
 
13.8%
1364
 
4.4%
2162
 
1.9%
3108
 
1.3%
472
 
0.9%
558
 
0.7%
746
 
0.6%
639
 
0.5%
833
 
0.4%
Other values (158)493
 
5.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_24aesc
Categorical

HIGH CARDINALITY

Distinct193
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1056 
1
 
334
2
 
190
3
 
106
Other values (188)
835 

Length

Max length6
Median length1
Mean length1.085858586
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)1.4%

Sample

1st row156136
2nd row544
3rd row278
4th row106
5th row83

Common Values

ValueCountFrequency (%)
*5795
69.7%
01056
 
12.7%
1334
 
4.0%
2190
 
2.3%
3106
 
1.3%
471
 
0.9%
563
 
0.8%
743
 
0.5%
842
 
0.5%
640
 
0.5%
Other values (183)576
 
6.9%

Length

2022-11-06T21:05:30.411145image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01056
 
12.7%
1334
 
4.0%
2190
 
2.3%
3106
 
1.3%
471
 
0.9%
563
 
0.8%
743
 
0.5%
842
 
0.5%
640
 
0.5%
Other values (183)576
 
6.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_24nesc
Categorical

HIGH CARDINALITY

Distinct305
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
1
 
240
0
 
231
2
 
216
3
 
199
Other values (300)
1635 

Length

Max length6
Median length1
Mean length1.174963925
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)1.9%

Sample

1st row271716
2nd row2875
3rd row1436
4th row334
5th row219

Common Values

ValueCountFrequency (%)
*5795
69.7%
1240
 
2.9%
0231
 
2.8%
2216
 
2.6%
3199
 
2.4%
4150
 
1.8%
5112
 
1.3%
689
 
1.1%
769
 
0.8%
860
 
0.7%
Other values (295)1155
 
13.9%

Length

2022-11-06T21:05:30.598143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1240
 
2.9%
0231
 
2.8%
2216
 
2.6%
3199
 
2.4%
4150
 
1.8%
5112
 
1.3%
689
 
1.1%
769
 
0.8%
860
 
0.7%
Other values (295)1155
 
13.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_sinstr
Categorical

HIGH CARDINALITY

Distinct208
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size472.2 KiB
*
5795 
0
 
373
1
 
344
2
 
274
3
 
193
Other values (203)
1337 

Length

Max length5
Median length1
Mean length1.128066378
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)1.4%

Sample

1st row90191
2nd row2116
3rd row916
4th row83
5th row47

Common Values

ValueCountFrequency (%)
*5795
69.7%
0373
 
4.5%
1344
 
4.1%
2274
 
3.3%
3193
 
2.3%
4134
 
1.6%
5104
 
1.3%
770
 
0.8%
657
 
0.7%
850
 
0.6%
Other values (198)922
 
11.1%

Length

2022-11-06T21:05:30.802145image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0373
 
4.5%
1344
 
4.1%
2274
 
3.3%
3193
 
2.3%
4134
 
1.6%
5104
 
1.3%
770
 
0.8%
657
 
0.7%
850
 
0.6%
Other values (198)922
 
11.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_sprima
Categorical

HIGH CARDINALITY

Distinct344
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size472.7 KiB
*
5795 
2
 
200
3
 
186
4
 
181
1
 
167
Other values (339)
1787 

Length

Max length6
Median length1
Mean length1.196849447
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)2.2%

Sample

1st row239858
2nd row4329
3rd row1869
4th row430
5th row280

Common Values

ValueCountFrequency (%)
*5795
69.7%
2200
 
2.4%
3186
 
2.2%
4181
 
2.2%
1167
 
2.0%
5152
 
1.8%
6127
 
1.5%
793
 
1.1%
082
 
1.0%
873
 
0.9%
Other values (334)1260
 
15.2%

Length

2022-11-06T21:05:30.988144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
2200
 
2.4%
3186
 
2.2%
4181
 
2.2%
1167
 
2.0%
5152
 
1.8%
6127
 
1.5%
793
 
1.1%
082
 
1.0%
873
 
0.9%
Other values (334)1260
 
15.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_cprima
Categorical

HIGH CARDINALITY

Distinct302
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size472.5 KiB
*
5795 
1
 
289
2
 
260
0
 
226
3
 
224
Other values (297)
1522 

Length

Max length6
Median length1
Mean length1.163419913
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)2.1%

Sample

1st row243165
2nd row2700
3rd row1333
4th row392
5th row293

Common Values

ValueCountFrequency (%)
*5795
69.7%
1289
 
3.5%
2260
 
3.1%
0226
 
2.7%
3224
 
2.7%
4145
 
1.7%
5110
 
1.3%
679
 
0.9%
755
 
0.7%
955
 
0.7%
Other values (292)1078
 
13.0%

Length

2022-11-06T21:05:31.146141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1289
 
3.5%
2260
 
3.1%
0226
 
2.7%
3224
 
2.7%
4145
 
1.7%
5110
 
1.3%
679
 
0.9%
755
 
0.7%
955
 
0.7%
Other values (292)1078
 
13.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_pospri
Categorical

HIGH CARDINALITY

Distinct409
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size472.8 KiB
*
5795 
2
 
212
3
 
199
1
 
199
0
 
170
Other values (404)
1741 

Length

Max length6
Median length1
Mean length1.202020202
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)3.1%

Sample

1st row900369
2nd row3685
3rd row2372
4th row754
5th row510

Common Values

ValueCountFrequency (%)
*5795
69.7%
2212
 
2.5%
3199
 
2.4%
1199
 
2.4%
0170
 
2.0%
4169
 
2.0%
5131
 
1.6%
696
 
1.2%
790
 
1.1%
867
 
0.8%
Other values (399)1188
 
14.3%

Length

2022-11-06T21:05:31.308143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
2212
 
2.5%
3199
 
2.4%
1199
 
2.4%
0170
 
2.0%
4169
 
2.0%
5131
 
1.6%
696
 
1.2%
790
 
1.1%
867
 
0.8%
Other values (399)1188
 
14.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_ssecu
Categorical

HIGH CARDINALITY

Distinct198
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size471.9 KiB
*
5795 
0
705 
1
 
429
2
 
229
3
 
165
Other values (193)
993 

Length

Max length6
Median length1
Mean length1.096440596
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)1.4%

Sample

1st row103681
2nd row797
3rd row493
4th row129
5th row72

Common Values

ValueCountFrequency (%)
*5795
69.7%
0705
 
8.5%
1429
 
5.2%
2229
 
2.8%
3165
 
2.0%
486
 
1.0%
581
 
1.0%
659
 
0.7%
746
 
0.6%
1045
 
0.5%
Other values (188)676
 
8.1%

Length

2022-11-06T21:05:31.467144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0705
 
8.5%
1429
 
5.2%
2229
 
2.8%
3165
 
2.0%
486
 
1.0%
581
 
1.0%
659
 
0.7%
746
 
0.6%
1045
 
0.5%
Other values (188)676
 
8.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_csecu
Categorical

HIGH CARDINALITY

Distinct292
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size472.3 KiB
*
5795 
0
 
411
1
 
369
2
 
272
3
 
172
Other values (287)
1297 

Length

Max length6
Median length1
Mean length1.143698894
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)2.0%

Sample

1st row303528
2nd row1694
3rd row1221
4th row322
5th row213

Common Values

ValueCountFrequency (%)
*5795
69.7%
0411
 
4.9%
1369
 
4.4%
2272
 
3.3%
3172
 
2.1%
4134
 
1.6%
599
 
1.2%
676
 
0.9%
841
 
0.5%
739
 
0.5%
Other values (282)908
 
10.9%

Length

2022-11-06T21:05:31.709146image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0411
 
4.9%
1369
 
4.4%
2272
 
3.3%
3172
 
2.1%
4134
 
1.6%
599
 
1.2%
676
 
0.9%
841
 
0.5%
739
 
0.5%
Other values (282)908
 
10.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_sinsec
Categorical

HIGH CARDINALITY

Distinct476
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size473.5 KiB
*
5795 
5
 
130
4
 
121
6
 
112
7
 
112
Other values (471)
2046 

Length

Max length6
Median length1
Mean length1.286556037
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique266 ?
Unique (%)3.2%

Sample

1st row573417
2nd row9145
3rd row4120
4th row905
5th row620

Common Values

ValueCountFrequency (%)
*5795
69.7%
5130
 
1.6%
4121
 
1.5%
6112
 
1.3%
7112
 
1.3%
8109
 
1.3%
999
 
1.2%
393
 
1.1%
1074
 
0.9%
1272
 
0.9%
Other values (466)1599
 
19.2%

Length

2022-11-06T21:05:31.893145image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
5130
 
1.6%
4121
 
1.5%
6112
 
1.3%
7112
 
1.3%
8109
 
1.3%
999
 
1.2%
393
 
1.1%
1074
 
0.9%
1272
 
0.9%
Other values (466)1599
 
19.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_consec
Categorical

HIGH CARDINALITY

Distinct339
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size472.5 KiB
*
5795 
1
 
306
2
 
259
0
 
231
3
 
200
Other values (334)
1525 

Length

Max length6
Median length1
Mean length1.168951419
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)2.5%

Sample

1st row420970
2nd row2518
3rd row1728
4th row461
5th row291

Common Values

ValueCountFrequency (%)
*5795
69.7%
1306
 
3.7%
2259
 
3.1%
0231
 
2.8%
3200
 
2.4%
4142
 
1.7%
5118
 
1.4%
683
 
1.0%
767
 
0.8%
863
 
0.8%
Other values (329)1052
 
12.7%

Length

2022-11-06T21:05:32.052144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1306
 
3.7%
2259
 
3.1%
0231
 
2.8%
3200
 
2.4%
4142
 
1.7%
5118
 
1.4%
683
 
1.0%
767
 
0.8%
863
 
0.8%
Other values (329)1052
 
12.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15_cmedss
Categorical

HIGH CARDINALITY

Distinct265
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
0
716 
1
 
387
2
 
251
3
 
153
Other values (260)
1014 

Length

Max length6
Median length1
Mean length1.115921116
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)1.9%

Sample

1st row479399
2nd row1167
3rd row644
4th row293
5th row219

Common Values

ValueCountFrequency (%)
*5795
69.7%
0716
 
8.6%
1387
 
4.7%
2251
 
3.0%
3153
 
1.8%
485
 
1.0%
564
 
0.8%
754
 
0.6%
654
 
0.6%
842
 
0.5%
Other values (255)715
 
8.6%

Length

2022-11-06T21:05:32.212141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0716
 
8.6%
1387
 
4.7%
2251
 
3.0%
3153
 
1.8%
485
 
1.0%
564
 
0.8%
754
 
0.6%
654
 
0.6%
842
 
0.5%
Other values (255)715
 
8.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18_smedsu
Categorical

HIGH CARDINALITY

Distinct522
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size473.7 KiB
*
5795 
6
 
148
7
 
116
5
 
113
8
 
107
Other values (517)
2037 

Length

Max length6
Median length1
Mean length1.317700818
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)3.4%

Sample

1st row905121
2nd row10784
3rd row5511
4th row1269
5th row842

Common Values

ValueCountFrequency (%)
*5795
69.7%
6148
 
1.8%
7116
 
1.4%
5113
 
1.4%
8107
 
1.3%
999
 
1.2%
1088
 
1.1%
1169
 
0.8%
461
 
0.7%
1255
 
0.7%
Other values (512)1665
 
20.0%

Length

2022-11-06T21:05:32.373140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
6148
 
1.8%
7116
 
1.4%
5113
 
1.4%
8107
 
1.3%
999
 
1.2%
1088
 
1.1%
1169
 
0.8%
461
 
0.7%
1255
 
0.7%
Other values (512)1665
 
20.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18_cmedsu
Categorical

HIGH CARDINALITY

Distinct214
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size471.9 KiB
*
5795 
0
875 
1
 
416
2
 
237
3
 
125
Other values (209)
868 

Length

Max length6
Median length1
Mean length1.092592593
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)1.5%

Sample

1st row253796
2nd row732
3rd row442
4th row175
5th row128

Common Values

ValueCountFrequency (%)
*5795
69.7%
0875
 
10.5%
1416
 
5.0%
2237
 
2.8%
3125
 
1.5%
488
 
1.1%
562
 
0.7%
749
 
0.6%
640
 
0.5%
834
 
0.4%
Other values (204)595
 
7.2%

Length

2022-11-06T21:05:32.535142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0875
 
10.5%
1416
 
5.0%
2237
 
2.8%
3125
 
1.5%
488
 
1.1%
562
 
0.7%
749
 
0.6%
640
 
0.5%
834
 
0.4%
Other values (204)595
 
7.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18_csuper
Categorical

HIGH CARDINALITY

Distinct164
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size471.6 KiB
*
5795 
0
1386 
1
 
332
2
 
132
3
 
95
Other values (159)
 
576

Length

Max length6
Median length1
Mean length1.05964406
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)1.3%

Sample

1st row183483
2nd row315
3rd row152
4th row73
5th row61

Common Values

ValueCountFrequency (%)
*5795
69.7%
01386
 
16.7%
1332
 
4.0%
2132
 
1.6%
395
 
1.1%
566
 
0.8%
461
 
0.7%
640
 
0.5%
730
 
0.4%
918
 
0.2%
Other values (154)361
 
4.3%

Length

2022-11-06T21:05:32.705140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01386
 
16.7%
1332
 
4.0%
2132
 
1.6%
395
 
1.1%
566
 
0.8%
461
 
0.7%
640
 
0.5%
730
 
0.4%
918
 
0.2%
Other values (154)361
 
4.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

gradoesco
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size471.2 KiB
*
5795 
5
722 
6
601 
4
 
368
7
 
326
Other values (11)
 
504

Length

Max length3
Median length1
Mean length1.007936508
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8
2nd row5
3rd row4
4th row7
5th row7

Common Values

ValueCountFrequency (%)
*5795
69.7%
5722
 
8.7%
6601
 
7.2%
4368
 
4.4%
7326
 
3.9%
3173
 
2.1%
8123
 
1.5%
279
 
0.9%
941
 
0.5%
131
 
0.4%
Other values (6)57
 
0.7%

Length

2022-11-06T21:05:33.045142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
5722
 
8.7%
6601
 
7.2%
4368
 
4.4%
7326
 
3.9%
3173
 
2.1%
8123
 
1.5%
279
 
0.9%
941
 
0.5%
131
 
0.4%
Other values (6)57
 
0.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

psolter12_
Categorical

HIGH CARDINALITY

Distinct388
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size473.0 KiB
*
5795 
2
 
191
3
 
181
1
 
155
4
 
151
Other values (383)
1843 

Length

Max length6
Median length1
Mean length1.222222222
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)2.6%

Sample

1st row586702
2nd row4833
3rd row2246
4th row672
5th row462

Common Values

ValueCountFrequency (%)
*5795
69.7%
2191
 
2.3%
3181
 
2.2%
1155
 
1.9%
4151
 
1.8%
5112
 
1.3%
6112
 
1.3%
0106
 
1.3%
779
 
0.9%
871
 
0.9%
Other values (378)1363
 
16.4%

Length

2022-11-06T21:05:33.258149image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
2191
 
2.3%
3181
 
2.2%
1155
 
1.9%
4151
 
1.8%
5112
 
1.3%
6112
 
1.3%
0106
 
1.3%
779
 
0.9%
871
 
0.9%
Other values (378)1363
 
16.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcasada12_
Categorical

HIGH CARDINALITY

Distinct480
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size473.4 KiB
*
5795 
6
 
230
4
 
154
8
 
151
10
 
102
Other values (475)
1884 

Length

Max length6
Median length1
Mean length1.281385281
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique273 ?
Unique (%)3.3%

Sample

1st row891481
2nd row7794
3rd row4060
4th row1048
5th row710

Common Values

ValueCountFrequency (%)
*5795
69.7%
6230
 
2.8%
4154
 
1.9%
8151
 
1.8%
10102
 
1.2%
1279
 
0.9%
775
 
0.9%
572
 
0.9%
271
 
0.9%
971
 
0.9%
Other values (470)1516
 
18.2%

Length

2022-11-06T21:05:33.465141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
6230
 
2.8%
4154
 
1.9%
8151
 
1.8%
10102
 
1.2%
1279
 
0.9%
775
 
0.9%
572
 
0.9%
271
 
0.9%
971
 
0.9%
Other values (470)1516
 
18.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_hli
Categorical

HIGH CARDINALITY

Distinct209
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1240 
1
 
285
2
 
160
3
 
81
Other values (204)
755 

Length

Max length5
Median length1
Mean length1.084896585
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)1.3%

Sample

1st row55694
2nd row925
3rd row378
4th row4
5th row4

Common Values

ValueCountFrequency (%)
*5795
69.7%
01240
 
14.9%
1285
 
3.4%
2160
 
1.9%
381
 
1.0%
466
 
0.8%
550
 
0.6%
836
 
0.4%
636
 
0.4%
729
 
0.3%
Other values (199)538
 
6.5%

Length

2022-11-06T21:05:33.707143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01240
 
14.9%
1285
 
3.4%
2160
 
1.9%
381
 
1.0%
466
 
0.8%
550
 
0.6%
836
 
0.4%
636
 
0.4%
729
 
0.3%
Other values (199)538
 
6.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_hliyne
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size471.2 KiB
*
5795 
0
2299 
1
 
75
2
 
30
3
 
27
Other values (38)
 
90

Length

Max length4
Median length1
Mean length1.00974026
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.3%

Sample

1st row1328
2nd row43
3rd row24
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5795
69.7%
02299
 
27.6%
175
 
0.9%
230
 
0.4%
327
 
0.3%
N/D15
 
0.2%
410
 
0.1%
67
 
0.1%
75
 
0.1%
114
 
< 0.1%
Other values (33)49
 
0.6%

Length

2022-11-06T21:05:33.929142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
02299
 
27.6%
175
 
0.9%
230
 
0.4%
327
 
0.3%
n/d15
 
0.2%
410
 
0.1%
67
 
0.1%
75
 
0.1%
54
 
< 0.1%
Other values (33)49
 
0.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_hliye
Categorical

HIGH CARDINALITY

Distinct212
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1262 
1
 
285
2
 
156
3
 
85
Other values (207)
733 

Length

Max length5
Median length1
Mean length1.082972583
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)1.5%

Sample

1st row53049
2nd row842
3rd row340
4th row4
5th row4

Common Values

ValueCountFrequency (%)
*5795
69.7%
01262
 
15.2%
1285
 
3.4%
2156
 
1.9%
385
 
1.0%
469
 
0.8%
540
 
0.5%
636
 
0.4%
831
 
0.4%
731
 
0.4%
Other values (202)526
 
6.3%

Length

2022-11-06T21:05:34.124139image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01262
 
15.2%
1285
 
3.4%
2156
 
1.9%
385
 
1.0%
469
 
0.8%
540
 
0.5%
636
 
0.4%
831
 
0.4%
731
 
0.4%
Other values (202)526
 
6.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_catolic
Categorical

HIGH CARDINALITY

Distinct634
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size474.2 KiB
*
5795 
10
 
91
9
 
86
11
 
76
8
 
69
Other values (629)
2199 

Length

Max length7
Median length1
Mean length1.372414622
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique381 ?
Unique (%)4.6%

Sample

1st row1718889
2nd row14158
3rd row6911
4th row2071
5th row1429

Common Values

ValueCountFrequency (%)
*5795
69.7%
1091
 
1.1%
986
 
1.0%
1176
 
0.9%
869
 
0.8%
1269
 
0.8%
764
 
0.8%
555
 
0.7%
1552
 
0.6%
1452
 
0.6%
Other values (624)1907
 
22.9%

Length

2022-11-06T21:05:34.406143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1091
 
1.1%
986
 
1.0%
1176
 
0.9%
869
 
0.8%
1269
 
0.8%
764
 
0.8%
555
 
0.7%
1552
 
0.6%
1452
 
0.6%
Other values (624)1907
 
22.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_ncatoli
Categorical

HIGH CARDINALITY

Distinct213
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size471.9 KiB
*
5795 
0
1342 
1
 
168
2
 
127
3
 
80
Other values (208)
804 

Length

Max length6
Median length1
Mean length1.086580087
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)1.6%

Sample

1st row131781
2nd row575
3rd row315
4th row48
5th row19

Common Values

ValueCountFrequency (%)
*5795
69.7%
01342
 
16.1%
1168
 
2.0%
2127
 
1.5%
380
 
1.0%
475
 
0.9%
550
 
0.6%
643
 
0.5%
741
 
0.5%
933
 
0.4%
Other values (203)562
 
6.8%

Length

2022-11-06T21:05:34.597144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01342
 
16.1%
1168
 
2.0%
2127
 
1.5%
380
 
1.0%
475
 
0.9%
550
 
0.6%
643
 
0.5%
741
 
0.5%
933
 
0.4%
Other values (203)562
 
6.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_sinreli
Categorical

HIGH CARDINALITY

Distinct270
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size472.2 KiB
*
5795 
0
898 
1
 
185
2
 
153
4
 
105
Other values (265)
1180 

Length

Max length6
Median length1
Mean length1.129389129
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)1.9%

Sample

1st row216988
2nd row1609
3rd row786
4th row86
5th row37

Common Values

ValueCountFrequency (%)
*5795
69.7%
0898
 
10.8%
1185
 
2.2%
2153
 
1.8%
4105
 
1.3%
3101
 
1.2%
573
 
0.9%
670
 
0.8%
763
 
0.8%
843
 
0.5%
Other values (260)830
 
10.0%

Length

2022-11-06T21:05:34.807140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0898
 
10.8%
1185
 
2.2%
2153
 
1.8%
4105
 
1.3%
3101
 
1.2%
573
 
0.9%
670
 
0.8%
763
 
0.8%
843
 
0.5%
Other values (260)830
 
10.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pecoactiv
Categorical

HIGH CARDINALITY

Distinct444
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size473.2 KiB
*
5795 
5
 
175
4
 
173
3
 
167
6
 
136
Other values (439)
1870 

Length

Max length6
Median length1
Mean length1.257816258
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique255 ?
Unique (%)3.1%

Sample

1st row819969
2nd row8113
3rd row4015
4th row858
5th row583

Common Values

ValueCountFrequency (%)
*5795
69.7%
5175
 
2.1%
4173
 
2.1%
3167
 
2.0%
6136
 
1.6%
8108
 
1.3%
7107
 
1.3%
978
 
0.9%
1066
 
0.8%
258
 
0.7%
Other values (434)1453
 
17.5%

Length

2022-11-06T21:05:35.015140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
5175
 
2.1%
4173
 
2.1%
3167
 
2.0%
6136
 
1.6%
8108
 
1.3%
7107
 
1.3%
978
 
0.9%
1066
 
0.8%
258
 
0.7%
Other values (434)1453
 
17.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pecoinact
Categorical

HIGH CARDINALITY

Distinct462
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size473.2 KiB
*
5795 
4
 
161
3
 
149
5
 
148
6
 
123
Other values (457)
1940 

Length

Max length6
Median length1
Mean length1.256132756
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)3.0%

Sample

1st row789609
2nd row5604
3rd row2786
4th row955
5th row650

Common Values

ValueCountFrequency (%)
*5795
69.7%
4161
 
1.9%
3149
 
1.8%
5148
 
1.8%
6123
 
1.5%
7114
 
1.4%
2106
 
1.3%
8102
 
1.2%
176
 
0.9%
965
 
0.8%
Other values (452)1477
 
17.8%

Length

2022-11-06T21:05:35.202145image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
4161
 
1.9%
3149
 
1.8%
5148
 
1.8%
6123
 
1.5%
7114
 
1.4%
2106
 
1.3%
8102
 
1.2%
176
 
0.9%
965
 
0.8%
Other values (452)1477
 
17.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocupada
Categorical

HIGH CARDINALITY

Distinct451
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size473.2 KiB
*
5795 
5
 
177
4
 
172
3
 
169
6
 
136
Other values (446)
1867 

Length

Max length6
Median length1
Mean length1.256734007
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique263 ?
Unique (%)3.2%

Sample

1st row810424
2nd row8081
3rd row3994
4th row856
5th row582

Common Values

ValueCountFrequency (%)
*5795
69.7%
5177
 
2.1%
4172
 
2.1%
3169
 
2.0%
6136
 
1.6%
8106
 
1.3%
7106
 
1.3%
982
 
1.0%
1063
 
0.8%
261
 
0.7%
Other values (441)1449
 
17.4%

Length

2022-11-06T21:05:35.391140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
5177
 
2.1%
4172
 
2.1%
3169
 
2.0%
6136
 
1.6%
8106
 
1.3%
7106
 
1.3%
982
 
1.0%
1063
 
0.8%
261
 
0.7%
Other values (441)1449
 
17.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocusecp
Categorical

HIGH CARDINALITY

Distinct323
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size472.7 KiB
*
5795 
3
 
210
4
 
190
5
 
172
2
 
147
Other values (318)
1802 

Length

Max length6
Median length1
Mean length1.193722944
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)2.1%

Sample

1st row128736
2nd row6340
3rd row2593
4th row257
5th row139

Common Values

ValueCountFrequency (%)
*5795
69.7%
3210
 
2.5%
4190
 
2.3%
5172
 
2.1%
2147
 
1.8%
6118
 
1.4%
196
 
1.2%
795
 
1.1%
084
 
1.0%
884
 
1.0%
Other values (313)1325
 
15.9%

Length

2022-11-06T21:05:35.580144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3210
 
2.5%
4190
 
2.3%
5172
 
2.1%
2147
 
1.8%
6118
 
1.4%
196
 
1.2%
795
 
1.1%
884
 
1.0%
084
 
1.0%
Other values (313)1325
 
15.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocusecs
Categorical

HIGH CARDINALITY

Distinct240
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
0
954 
1
 
290
2
 
175
3
 
131
Other values (235)
971 

Length

Max length6
Median length1
Mean length1.109427609
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)1.7%

Sample

1st row238225
2nd row750
3rd row809
4th row332
5th row258

Common Values

ValueCountFrequency (%)
*5795
69.7%
0954
 
11.5%
1290
 
3.5%
2175
 
2.1%
3131
 
1.6%
482
 
1.0%
567
 
0.8%
644
 
0.5%
741
 
0.5%
835
 
0.4%
Other values (230)702
 
8.4%

Length

2022-11-06T21:05:35.788140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0954
 
11.5%
1290
 
3.5%
2175
 
2.1%
3131
 
1.6%
482
 
1.0%
567
 
0.8%
644
 
0.5%
741
 
0.5%
835
 
0.4%
Other values (230)702
 
8.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocusect
Categorical

HIGH CARDINALITY

Distinct253
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
0
794 
1
 
396
2
 
210
3
 
116
Other values (248)
1005 

Length

Max length6
Median length1
Mean length1.116281866
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)1.8%

Sample

1st row415558
2nd row887
3rd row521
4th row240
5th row167

Common Values

ValueCountFrequency (%)
*5795
69.7%
0794
 
9.5%
1396
 
4.8%
2210
 
2.5%
3116
 
1.4%
482
 
1.0%
569
 
0.8%
654
 
0.6%
745
 
0.5%
838
 
0.5%
Other values (243)717
 
8.6%

Length

2022-11-06T21:05:35.964143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0794
 
9.5%
1396
 
4.8%
2210
 
2.5%
3116
 
1.4%
482
 
1.0%
569
 
0.8%
654
 
0.6%
745
 
0.5%
838
 
0.5%
Other values (243)717
 
8.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocuningr
Categorical

HIGH CARDINALITY

Distinct133
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size471.6 KiB
*
5795 
0
1325 
1
 
271
2
 
181
3
 
110
Other values (128)
634 

Length

Max length5
Median length1
Mean length1.054232804
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)0.9%

Sample

1st row18282
2nd row572
3rd row241
4th row64
5th row37

Common Values

ValueCountFrequency (%)
*5795
69.7%
01325
 
15.9%
1271
 
3.3%
2181
 
2.2%
3110
 
1.3%
568
 
0.8%
468
 
0.8%
649
 
0.6%
732
 
0.4%
1129
 
0.3%
Other values (123)388
 
4.7%

Length

2022-11-06T21:05:36.173144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01325
 
15.9%
1271
 
3.3%
2181
 
2.2%
3110
 
1.3%
568
 
0.8%
468
 
0.8%
649
 
0.6%
732
 
0.4%
1129
 
0.3%
Other values (123)388
 
4.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_1sm
Categorical

HIGH CARDINALITY

Distinct178
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1070 
1
 
326
2
 
172
3
 
97
Other values (173)
856 

Length

Max length5
Median length1
Mean length1.082371332
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)1.3%

Sample

1st row54652
2nd row619
3rd row631
4th row74
5th row57

Common Values

ValueCountFrequency (%)
*5795
69.7%
01070
 
12.9%
1326
 
3.9%
2172
 
2.1%
397
 
1.2%
483
 
1.0%
563
 
0.8%
648
 
0.6%
744
 
0.5%
836
 
0.4%
Other values (168)582
 
7.0%

Length

2022-11-06T21:05:36.467144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01070
 
12.9%
1326
 
3.9%
2172
 
2.1%
397
 
1.2%
483
 
1.0%
563
 
0.8%
648
 
0.6%
744
 
0.5%
836
 
0.4%
Other values (168)582
 
7.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p1_2sm
Categorical

HIGH CARDINALITY

Distinct325
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
1
 
277
2
 
239
3
 
194
4
 
163
Other values (320)
1648 

Length

Max length6
Median length1
Mean length1.174603175
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)2.1%

Sample

1st row258959
2nd row4066
3rd row1593
4th row391
5th row276

Common Values

ValueCountFrequency (%)
*5795
69.7%
1277
 
3.3%
2239
 
2.9%
3194
 
2.3%
4163
 
2.0%
0158
 
1.9%
5127
 
1.5%
693
 
1.1%
780
 
1.0%
854
 
0.6%
Other values (315)1136
 
13.7%

Length

2022-11-06T21:05:36.736142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1277
 
3.3%
2239
 
2.9%
3194
 
2.3%
4163
 
2.0%
0158
 
1.9%
5127
 
1.5%
693
 
1.1%
780
 
1.0%
854
 
0.6%
Other values (315)1136
 
13.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p2_5sm
Categorical

HIGH CARDINALITY

Distinct257
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size472.2 KiB
*
5795 
0
 
357
1
 
347
2
 
286
3
 
205
Other values (252)
1326 

Length

Max length6
Median length1
Mean length1.126984127
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)1.7%

Sample

1st row324851
2nd row2235
3rd row1238
4th row240
5th row158

Common Values

ValueCountFrequency (%)
*5795
69.7%
0357
 
4.3%
1347
 
4.2%
2286
 
3.4%
3205
 
2.5%
4162
 
1.9%
5118
 
1.4%
690
 
1.1%
771
 
0.9%
860
 
0.7%
Other values (247)825
 
9.9%

Length

2022-11-06T21:05:36.950141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0357
 
4.3%
1347
 
4.2%
2286
 
3.4%
3205
 
2.5%
4162
 
1.9%
5118
 
1.4%
690
 
1.1%
771
 
0.9%
860
 
0.7%
Other values (247)825
 
9.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6_10sm
Categorical

HIGH CARDINALITY

Distinct128
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size471.5 KiB
*
5795 
0
1578 
1
 
361
2
 
133
3
 
71
Other values (123)
 
378

Length

Max length5
Median length1
Mean length1.042207792
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.0%

Sample

1st row77403
2nd row171
3rd row69
4th row30
5th row20

Common Values

ValueCountFrequency (%)
*5795
69.7%
01578
 
19.0%
1361
 
4.3%
2133
 
1.6%
371
 
0.9%
445
 
0.5%
536
 
0.4%
821
 
0.3%
617
 
0.2%
N/D15
 
0.2%
Other values (118)244
 
2.9%

Length

2022-11-06T21:05:37.495144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01578
 
19.0%
1361
 
4.3%
2133
 
1.6%
371
 
0.9%
445
 
0.5%
536
 
0.4%
821
 
0.3%
617
 
0.2%
n/d15
 
0.2%
Other values (118)244
 
2.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p10_sm
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct97
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
1891 
1
 
246
2
 
89
3
 
48
Other values (92)
 
247

Length

Max length5
Median length1
Mean length1.025372775
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)0.8%

Sample

1st row34030
2nd row88
3rd row37
4th row12
5th row9

Common Values

ValueCountFrequency (%)
*5795
69.7%
01891
 
22.7%
1246
 
3.0%
289
 
1.1%
348
 
0.6%
533
 
0.4%
429
 
0.3%
N/D15
 
0.2%
715
 
0.2%
612
 
0.1%
Other values (87)143
 
1.7%

Length

2022-11-06T21:05:37.955143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01891
 
22.7%
1246
 
3.0%
289
 
1.1%
348
 
0.6%
533
 
0.4%
429
 
0.3%
n/d15
 
0.2%
715
 
0.2%
612
 
0.1%
Other values (87)143
 
1.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnotraba
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct90
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
1647 
1
 
335
2
 
149
3
 
74
Other values (85)
 
316

Length

Max length5
Median length1
Mean length1.025132275
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)0.6%

Sample

1st row12666
2nd row79
3rd row43
4th row20
5th row12

Common Values

ValueCountFrequency (%)
*5795
69.7%
01647
 
19.8%
1335
 
4.0%
2149
 
1.8%
374
 
0.9%
457
 
0.7%
531
 
0.4%
628
 
0.3%
725
 
0.3%
N/D15
 
0.2%
Other values (80)160
 
1.9%

Length

2022-11-06T21:05:38.214149image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01647
 
19.8%
1335
 
4.0%
2149
 
1.8%
374
 
0.9%
457
 
0.7%
531
 
0.4%
628
 
0.3%
725
 
0.3%
n/d15
 
0.2%
Other values (80)160
 
1.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_32htra
Categorical

HIGH CARDINALITY

Distinct217
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
0
849 
1
 
362
2
 
189
3
 
131
Other values (212)
990 

Length

Max length6
Median length1
Mean length1.100769601
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)1.6%

Sample

1st row119046
2nd row786
3rd row415
4th row150
5th row109

Common Values

ValueCountFrequency (%)
*5795
69.7%
0849
 
10.2%
1362
 
4.4%
2189
 
2.3%
3131
 
1.6%
493
 
1.1%
569
 
0.8%
663
 
0.8%
749
 
0.6%
846
 
0.6%
Other values (207)670
 
8.1%

Length

2022-11-06T21:05:38.487141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0849
 
10.2%
1362
 
4.4%
2189
 
2.3%
3131
 
1.6%
493
 
1.1%
569
 
0.8%
663
 
0.8%
749
 
0.6%
846
 
0.6%
Other values (207)670
 
8.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p33_40htr
Categorical

HIGH CARDINALITY

Distinct198
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size471.9 KiB
*
5795 
0
961 
1
 
362
2
 
189
3
 
125
Other values (193)
884 

Length

Max length6
Median length1
Mean length1.089225589
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)1.3%

Sample

1st row145240
2nd row770
3rd row377
4th row188
5th row72

Common Values

ValueCountFrequency (%)
*5795
69.7%
0961
 
11.6%
1362
 
4.4%
2189
 
2.3%
3125
 
1.5%
496
 
1.2%
564
 
0.8%
645
 
0.5%
745
 
0.5%
942
 
0.5%
Other values (188)592
 
7.1%

Length

2022-11-06T21:05:38.710140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0961
 
11.6%
1362
 
4.4%
2189
 
2.3%
3125
 
1.5%
496
 
1.2%
564
 
0.8%
745
 
0.5%
645
 
0.5%
942
 
0.5%
Other values (188)592
 
7.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p41_48htr
Categorical

HIGH CARDINALITY

Distinct304
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size472.5 KiB
*
5795 
0
 
258
1
 
245
2
 
216
3
 
190
Other values (299)
1612 

Length

Max length6
Median length1
Mean length1.16955267
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)2.0%

Sample

1st row303559
2nd row3169
3rd row1762
4th row362
5th row319

Common Values

ValueCountFrequency (%)
*5795
69.7%
0258
 
3.1%
1245
 
2.9%
2216
 
2.6%
3190
 
2.3%
4156
 
1.9%
5108
 
1.3%
689
 
1.1%
776
 
0.9%
866
 
0.8%
Other values (294)1117
 
13.4%

Length

2022-11-06T21:05:38.955141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0258
 
3.1%
1245
 
2.9%
2216
 
2.6%
3190
 
2.3%
4156
 
1.9%
5108
 
1.3%
689
 
1.1%
776
 
0.9%
866
 
0.8%
Other values (294)1117
 
13.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p48_htr
Categorical

HIGH CARDINALITY

Distinct241
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
0
 
424
1
 
342
2
 
283
3
 
198
Other values (236)
1274 

Length

Max length6
Median length1
Mean length1.12037037
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)1.7%

Sample

1st row198088
2nd row3054
3rd row1321
4th row101
5th row47

Common Values

ValueCountFrequency (%)
*5795
69.7%
0424
 
5.1%
1342
 
4.1%
2283
 
3.4%
3198
 
2.4%
4162
 
1.9%
5115
 
1.4%
684
 
1.0%
756
 
0.7%
849
 
0.6%
Other values (231)808
 
9.7%

Length

2022-11-06T21:05:39.283144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0424
 
5.1%
1342
 
4.1%
2283
 
3.4%
3198
 
2.4%
4162
 
1.9%
5115
 
1.4%
684
 
1.0%
756
 
0.7%
849
 
0.6%
Other values (231)808
 
9.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

totvivhab
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct373
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean193.0025253
Minimum1
Maximum530435
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.1 KiB
2022-11-06T21:05:39.451141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile88
Maximum530435
Range530434
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6413.062061
Coefficient of variation (CV)33.22786607
Kurtosis5682.614129
Mean193.0025253
Median Absolute Deviation (MAD)0
Skewness71.04097373
Sum1605009
Variance41127364.99
MonotonicityNot monotonic
2022-11-06T21:05:39.719141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14752
57.1%
21060
 
12.7%
3453
 
5.4%
4278
 
3.3%
5176
 
2.1%
6123
 
1.5%
786
 
1.0%
878
 
0.9%
970
 
0.8%
1048
 
0.6%
Other values (363)1192
 
14.3%
ValueCountFrequency (%)
14752
57.1%
21060
 
12.7%
3453
 
5.4%
4278
 
3.3%
5176
 
2.1%
6123
 
1.5%
786
 
1.0%
878
 
0.9%
970
 
0.8%
1048
 
0.6%
ValueCountFrequency (%)
5304351
< 0.1%
1472721
< 0.1%
1332831
< 0.1%
860261
< 0.1%
607671
< 0.1%
377411
< 0.1%
372491
< 0.1%
353471
< 0.1%
319771
< 0.1%
310541
< 0.1%

vivparhab
Categorical

HIGH CARDINALITY

Distinct376
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size472.8 KiB
*
5795 
3
 
457
4
 
266
5
 
170
6
 
114
Other values (371)
1514 

Length

Max length6
Median length1
Mean length1.208633959
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)2.7%

Sample

1st row527427
2nd row4695
3rd row2040
4th row574
5th row392

Common Values

ValueCountFrequency (%)
*5795
69.7%
3457
 
5.5%
4266
 
3.2%
5170
 
2.0%
6114
 
1.4%
786
 
1.0%
882
 
1.0%
964
 
0.8%
1048
 
0.6%
239
 
0.5%
Other values (366)1195
 
14.4%

Length

2022-11-06T21:05:39.948157image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3457
 
5.5%
4266
 
3.2%
5170
 
2.0%
6114
 
1.4%
786
 
1.0%
882
 
1.0%
964
 
0.8%
1048
 
0.6%
239
 
0.5%
Other values (366)1195
 
14.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

ocuvivpar
Categorical

HIGH CARDINALITY

Distinct684
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size474.5 KiB
*
5795 
12
 
85
13
 
79
11
 
65
9
 
57
Other values (679)
2235 

Length

Max length7
Median length1
Mean length1.408369408
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique413 ?
Unique (%)5.0%

Sample

1st row2186002
2nd row15169
3rd row7296
4th row2398
5th row1630

Common Values

ValueCountFrequency (%)
*5795
69.7%
1285
 
1.0%
1379
 
0.9%
1165
 
0.8%
957
 
0.7%
856
 
0.7%
1856
 
0.7%
1654
 
0.6%
1054
 
0.6%
1450
 
0.6%
Other values (674)1965
 
23.6%

Length

2022-11-06T21:05:40.132153image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1285
 
1.0%
1379
 
0.9%
1165
 
0.8%
957
 
0.7%
856
 
0.7%
1856
 
0.7%
1654
 
0.6%
1054
 
0.6%
1450
 
0.6%
Other values (674)1965
 
23.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pro_ovp
Categorical

HIGH CARDINALITY

Distinct380
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size477.0 KiB
*
5795 
4
 
127
3
 
80
5
 
75
3.67
 
62
Other values (375)
2177 

Length

Max length5
Median length1
Mean length1.724867725
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)1.2%

Sample

1st row4.14
2nd row3.23
3rd row3.58
4th row4.18
5th row4.16

Common Values

ValueCountFrequency (%)
*5795
69.7%
4127
 
1.5%
380
 
1.0%
575
 
0.9%
3.6762
 
0.7%
4.3359
 
0.7%
3.3351
 
0.6%
2.6747
 
0.6%
4.547
 
0.6%
245
 
0.5%
Other values (370)1928
 
23.2%

Length

2022-11-06T21:05:40.385140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
4127
 
1.5%
380
 
1.0%
575
 
0.9%
3.6762
 
0.7%
4.3359
 
0.7%
3.3351
 
0.6%
2.6747
 
0.6%
4.547
 
0.6%
245
 
0.5%
Other values (370)1928
 
23.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pro_ocvp
Categorical

HIGH CARDINALITY

Distinct327
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size477.6 KiB
*
5795 
2
 
80
1
 
63
1.5
 
39
1.33
 
34
Other values (322)
2305 

Length

Max length4
Median length1
Mean length1.794011544
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)0.8%

Sample

1st row1.37
2nd row1.76
3rd row2.09
4th row1.3
5th row1.28

Common Values

ValueCountFrequency (%)
*5795
69.7%
280
 
1.0%
163
 
0.8%
1.539
 
0.5%
1.3334
 
0.4%
334
 
0.4%
2.534
 
0.4%
1.6730
 
0.4%
1.327
 
0.3%
1.827
 
0.3%
Other values (317)2153
 
25.9%

Length

2022-11-06T21:05:40.674140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
280
 
1.0%
163
 
0.8%
1.539
 
0.5%
1.3334
 
0.4%
334
 
0.4%
2.534
 
0.4%
1.6730
 
0.4%
1.327
 
0.3%
1.827
 
0.3%
Other values (317)2153
 
25.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_pardes
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct94
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
1816 
1
 
245
2
 
120
3
 
62
Other values (89)
 
278

Length

Max length5
Median length1
Mean length1.025974026
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)0.7%

Sample

1st row20137
2nd row170
3rd row75
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5795
69.7%
01816
 
21.8%
1245
 
2.9%
2120
 
1.4%
362
 
0.7%
442
 
0.5%
531
 
0.4%
721
 
0.3%
620
 
0.2%
N/D15
 
0.2%
Other values (84)149
 
1.8%

Length

2022-11-06T21:05:40.964144image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01816
 
21.8%
1245
 
2.9%
2120
 
1.4%
362
 
0.7%
442
 
0.5%
531
 
0.4%
721
 
0.3%
620
 
0.2%
n/d15
 
0.2%
Other values (84)149
 
1.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_tecdes
Categorical

HIGH CARDINALITY

Distinct163
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1102 
1
 
335
2
 
164
3
 
119
Other values (158)
801 

Length

Max length5
Median length1
Mean length1.075637326
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)1.1%

Sample

1st row50389
2nd row479
3rd row244
4th row43
5th row35

Common Values

ValueCountFrequency (%)
*5795
69.7%
01102
 
13.3%
1335
 
4.0%
2164
 
2.0%
3119
 
1.4%
479
 
0.9%
755
 
0.7%
554
 
0.6%
642
 
0.5%
840
 
0.5%
Other values (153)531
 
6.4%

Length

2022-11-06T21:05:41.225142image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01102
 
13.3%
1335
 
4.0%
2164
 
2.0%
3119
 
1.4%
479
 
0.9%
755
 
0.7%
554
 
0.6%
642
 
0.5%
840
 
0.5%
Other values (153)531
 
6.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_pisdes
Categorical

HIGH CARDINALITY

Distinct335
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size472.5 KiB
*
5795 
3
 
377
4
 
205
2
 
179
0
 
172
Other values (330)
1588 

Length

Max length6
Median length1
Mean length1.167508418
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)2.5%

Sample

1st row460045
2nd row3730
3rd row1563
4th row537
5th row368

Common Values

ValueCountFrequency (%)
*5795
69.7%
3377
 
4.5%
4205
 
2.5%
2179
 
2.2%
0172
 
2.1%
5157
 
1.9%
1152
 
1.8%
696
 
1.2%
873
 
0.9%
768
 
0.8%
Other values (325)1042
 
12.5%

Length

2022-11-06T21:05:41.450146image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3377
 
4.5%
4205
 
2.5%
2179
 
2.2%
0172
 
2.1%
5157
 
1.9%
1152
 
1.8%
696
 
1.2%
873
 
0.9%
768
 
0.8%
Other values (325)1042
 
12.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_ccuart
Categorical

HIGH CARDINALITY

Distinct198
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
1
 
395
0
 
380
2
 
342
3
 
228
Other values (193)
1176 

Length

Max length5
Median length1
Mean length1.109307359
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)1.4%

Sample

1st row97547
2nd row1223
3rd row610
4th row92
5th row62

Common Values

ValueCountFrequency (%)
*5795
69.7%
1395
 
4.7%
0380
 
4.6%
2342
 
4.1%
3228
 
2.7%
4134
 
1.6%
587
 
1.0%
669
 
0.8%
753
 
0.6%
1049
 
0.6%
Other values (188)784
 
9.4%

Length

2022-11-06T21:05:41.631141image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1395
 
4.7%
0380
 
4.6%
2342
 
4.1%
3228
 
2.7%
4134
 
1.6%
587
 
1.0%
669
 
0.8%
753
 
0.6%
949
 
0.6%
Other values (188)784
 
9.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp2_5cuar
Categorical

HIGH CARDINALITY

Distinct334
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
3
 
313
2
 
312
1
 
205
4
 
195
Other values (329)
1496 

Length

Max length6
Median length1
Mean length1.174963925
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)2.4%

Sample

1st row395268
2nd row3307
3rd row1350
4th row432
5th row297

Common Values

ValueCountFrequency (%)
*5795
69.7%
3313
 
3.8%
2312
 
3.8%
1205
 
2.5%
4195
 
2.3%
5121
 
1.5%
695
 
1.1%
062
 
0.7%
756
 
0.7%
852
 
0.6%
Other values (324)1110
 
13.3%

Length

2022-11-06T21:05:41.821140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3313
 
3.8%
2312
 
3.8%
1205
 
2.5%
4195
 
2.3%
5121
 
1.5%
695
 
1.1%
062
 
0.7%
756
 
0.7%
852
 
0.6%
Other values (324)1110
 
13.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_2cuar
Categorical

HIGH CARDINALITY

Distinct191
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
1
 
456
0
 
447
2
 
319
3
 
186
Other values (186)
1113 

Length

Max length5
Median length1
Mean length1.104377104
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)1.4%

Sample

1st row82169
2nd row1083
3rd row498
4th row81
5th row57

Common Values

ValueCountFrequency (%)
*5795
69.7%
1456
 
5.5%
0447
 
5.4%
2319
 
3.8%
3186
 
2.2%
4124
 
1.5%
590
 
1.1%
759
 
0.7%
656
 
0.7%
840
 
0.5%
Other values (181)744
 
8.9%

Length

2022-11-06T21:05:42.018139image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1456
 
5.5%
0447
 
5.4%
2319
 
3.8%
3186
 
2.2%
4124
 
1.5%
590
 
1.1%
759
 
0.7%
656
 
0.7%
840
 
0.5%
Other values (181)744
 
8.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

v_1cuarto
Categorical

HIGH CARDINALITY

Distinct133
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size471.6 KiB
*
5795 
0
882 
1
 
489
2
 
254
3
 
149
Other values (128)
747 

Length

Max length5
Median length1
Mean length1.061327561
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)0.9%

Sample

1st row38224
2nd row451
3rd row246
4th row33
5th row21

Common Values

ValueCountFrequency (%)
*5795
69.7%
0882
 
10.6%
1489
 
5.9%
2254
 
3.1%
3149
 
1.8%
494
 
1.1%
574
 
0.9%
662
 
0.7%
847
 
0.6%
1035
 
0.4%
Other values (123)435
 
5.2%

Length

2022-11-06T21:05:42.219140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0882
 
10.6%
1489
 
5.9%
2254
 
3.1%
3149
 
1.8%
494
 
1.1%
574
 
0.9%
662
 
0.7%
847
 
0.6%
1035
 
0.4%
Other values (123)435
 
5.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_cocgas
Categorical

HIGH CARDINALITY

Distinct343
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size472.5 KiB
*
5795 
3
 
325
0
 
256
2
 
228
1
 
195
Other values (338)
1517 

Length

Max length6
Median length1
Mean length1.162097162
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique208 ?
Unique (%)2.5%

Sample

1st row487090
2nd row2686
3rd row1308
4th row497
5th row347

Common Values

ValueCountFrequency (%)
*5795
69.7%
3325
 
3.9%
0256
 
3.1%
2228
 
2.7%
1195
 
2.3%
4188
 
2.3%
5134
 
1.6%
695
 
1.1%
860
 
0.7%
760
 
0.7%
Other values (333)980
 
11.8%

Length

2022-11-06T21:05:42.474140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3325
 
3.9%
0256
 
3.1%
2228
 
2.7%
1195
 
2.3%
4188
 
2.3%
5134
 
1.6%
695
 
1.1%
760
 
0.7%
860
 
0.7%
Other values (333)980
 
11.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_coclen
Categorical

HIGH CARDINALITY

Distinct177
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
0
 
569
1
 
296
3
 
228
2
 
219
Other values (172)
1209 

Length

Max length5
Median length1
Mean length1.108946609
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)1.0%

Sample

1st row33627
2nd row1949
3rd row705
4th row74
5th row45

Common Values

ValueCountFrequency (%)
*5795
69.7%
0569
 
6.8%
1296
 
3.6%
3228
 
2.7%
2219
 
2.6%
4125
 
1.5%
580
 
1.0%
670
 
0.8%
763
 
0.8%
858
 
0.7%
Other values (167)813
 
9.8%

Length

2022-11-06T21:05:42.687143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0569
 
6.8%
1296
 
3.6%
3228
 
2.7%
2219
 
2.6%
4125
 
1.5%
580
 
1.0%
670
 
0.8%
763
 
0.8%
858
 
0.7%
Other values (167)813
 
9.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_coccar
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size471.2 KiB
*
5795 
0
2441 
1
 
42
N/D
 
15
2
 
5
Other values (13)
 
18

Length

Max length3
Median length1
Mean length1.004689755
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row132
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5795
69.7%
02441
29.4%
142
 
0.5%
N/D15
 
0.2%
25
 
0.1%
63
 
< 0.1%
172
 
< 0.1%
72
 
< 0.1%
52
 
< 0.1%
41
 
< 0.1%
Other values (8)8
 
0.1%

Length

2022-11-06T21:05:42.889143image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
02441
29.4%
142
 
0.5%
n/d15
 
0.2%
25
 
0.1%
63
 
< 0.1%
72
 
< 0.1%
172
 
< 0.1%
52
 
< 0.1%
91
 
< 0.1%
Other values (8)8
 
0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_cocpet
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size471.2 KiB
*
5795 
0
2425 
1
 
51
N/D
 
15
2
 
11
Other values (11)
 
19

Length

Max length3
Median length1
Mean length1.004449254
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st row111
2nd row7
3rd row4
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5795
69.7%
02425
29.2%
151
 
0.6%
N/D15
 
0.2%
211
 
0.1%
34
 
< 0.1%
54
 
< 0.1%
132
 
< 0.1%
42
 
< 0.1%
91
 
< 0.1%
Other values (6)6
 
0.1%

Length

2022-11-06T21:05:43.101140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
02425
29.2%
151
 
0.6%
n/d15
 
0.2%
211
 
0.1%
54
 
< 0.1%
34
 
< 0.1%
42
 
< 0.1%
132
 
< 0.1%
71
 
< 0.1%
Other values (6)6
 
0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_sersan
Categorical

HIGH CARDINALITY

Distinct347
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
3
 
358
2
 
229
4
 
201
0
 
144
Other values (342)
1589 

Length

Max length6
Median length1
Mean length1.182058682
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)2.3%

Sample

1st row492978
2nd row3304
3rd row1436
4th row518
5th row356

Common Values

ValueCountFrequency (%)
*5795
69.7%
3358
 
4.3%
2229
 
2.8%
4201
 
2.4%
0144
 
1.7%
1131
 
1.6%
5114
 
1.4%
690
 
1.1%
767
 
0.8%
859
 
0.7%
Other values (337)1128
 
13.6%

Length

2022-11-06T21:05:43.283680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3358
 
4.3%
2229
 
2.8%
4201
 
2.4%
0144
 
1.7%
1131
 
1.6%
5114
 
1.4%
690
 
1.1%
767
 
0.8%
859
 
0.7%
Other values (337)1128
 
13.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_aguent
Categorical

HIGH CARDINALITY

Distinct350
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
0
 
466
3
 
240
2
 
166
1
 
149
Other values (345)
1500 

Length

Max length6
Median length1
Mean length1.179172679
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)2.4%

Sample

1st row483057
2nd row1860
3rd row967
4th row558
5th row384

Common Values

ValueCountFrequency (%)
*5795
69.7%
0466
 
5.6%
3240
 
2.9%
2166
 
2.0%
1149
 
1.8%
4144
 
1.7%
5108
 
1.3%
687
 
1.0%
841
 
0.5%
741
 
0.5%
Other values (340)1079
 
13.0%

Length

2022-11-06T21:05:43.467683image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0466
 
5.6%
3240
 
2.9%
2166
 
2.0%
1149
 
1.8%
4144
 
1.7%
5108
 
1.3%
687
 
1.0%
841
 
0.5%
741
 
0.5%
Other values (340)1079
 
13.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_drenaj
Categorical

HIGH CARDINALITY

Distinct289
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
0
731 
1
 
306
2
 
251
3
 
207
Other values (284)
1026 

Length

Max length6
Median length1
Mean length1.116281866
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)2.4%

Sample

1st row417595
2nd row1855
3rd row849
4th row532
5th row363

Common Values

ValueCountFrequency (%)
*5795
69.7%
0731
 
8.8%
1306
 
3.7%
2251
 
3.0%
3207
 
2.5%
4103
 
1.2%
593
 
1.1%
665
 
0.8%
745
 
0.5%
836
 
0.4%
Other values (279)684
 
8.2%

Length

2022-11-06T21:05:43.639680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0731
 
8.8%
1306
 
3.7%
2251
 
3.0%
3207
 
2.5%
4103
 
1.2%
593
 
1.1%
665
 
0.8%
745
 
0.5%
836
 
0.4%
Other values (279)684
 
8.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_electr
Categorical

HIGH CARDINALITY

Distinct364
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size472.7 KiB
*
5795 
3
 
323
0
 
206
4
 
206
5
 
146
Other values (359)
1640 

Length

Max length6
Median length1
Mean length1.192520443
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)2.5%

Sample

1st row506906
2nd row2539
3rd row1371
4th row556
5th row382

Common Values

ValueCountFrequency (%)
*5795
69.7%
3323
 
3.9%
0206
 
2.5%
4206
 
2.5%
5146
 
1.8%
2123
 
1.5%
695
 
1.1%
190
 
1.1%
779
 
0.9%
861
 
0.7%
Other values (354)1192
 
14.3%

Length

2022-11-06T21:05:43.839679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3323
 
3.9%
0206
 
2.5%
4206
 
2.5%
5146
 
1.8%
2123
 
1.5%
695
 
1.1%
190
 
1.1%
779
 
0.9%
861
 
0.7%
Other values (354)1192
 
14.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_dreagu
Categorical

HIGH CARDINALITY

Distinct283
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
0
904 
1
 
304
2
 
203
3
 
178
Other values (278)
932 

Length

Max length6
Median length1
Mean length1.110509861
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)2.3%

Sample

1st row402086
2nd row1235
3rd row625
4th row524
5th row359

Common Values

ValueCountFrequency (%)
*5795
69.7%
0904
 
10.9%
1304
 
3.7%
2203
 
2.4%
3178
 
2.1%
583
 
1.0%
481
 
1.0%
655
 
0.7%
836
 
0.4%
735
 
0.4%
Other values (273)642
 
7.7%

Length

2022-11-06T21:05:44.029684image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0904
 
10.9%
1304
 
3.7%
2203
 
2.4%
3178
 
2.1%
583
 
1.0%
481
 
1.0%
655
 
0.7%
836
 
0.4%
735
 
0.4%
Other values (273)642
 
7.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_dreele
Categorical

HIGH CARDINALITY

Distinct275
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
0
804 
1
 
303
2
 
234
3
 
191
Other values (270)
989 

Length

Max length6
Median length1
Mean length1.113155363
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)2.1%

Sample

1st row413544
2nd row1326
3rd row719
4th row522
5th row358

Common Values

ValueCountFrequency (%)
*5795
69.7%
0804
 
9.7%
1303
 
3.6%
2234
 
2.8%
3191
 
2.3%
4103
 
1.2%
582
 
1.0%
662
 
0.7%
745
 
0.5%
935
 
0.4%
Other values (265)662
 
8.0%

Length

2022-11-06T21:05:44.226681image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0804
 
9.7%
1303
 
3.6%
2234
 
2.8%
3191
 
2.3%
4103
 
1.2%
582
 
1.0%
662
 
0.7%
745
 
0.5%
935
 
0.4%
Other values (265)662
 
8.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_aguele
Categorical

HIGH CARDINALITY

Distinct355
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size472.5 KiB
*
5795 
0
 
555
3
 
216
1
 
151
4
 
148
Other values (350)
1451 

Length

Max length6
Median length1
Mean length1.171236171
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)2.5%

Sample

1st row474450
2nd row1356
3rd row825
4th row544
5th row375

Common Values

ValueCountFrequency (%)
*5795
69.7%
0555
 
6.7%
3216
 
2.6%
1151
 
1.8%
4148
 
1.8%
2148
 
1.8%
5108
 
1.3%
681
 
1.0%
744
 
0.5%
839
 
0.5%
Other values (345)1031
 
12.4%

Length

2022-11-06T21:05:44.564683image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0555
 
6.7%
3216
 
2.6%
1151
 
1.8%
4148
 
1.8%
2148
 
1.8%
5108
 
1.3%
681
 
1.0%
744
 
0.5%
839
 
0.5%
Other values (345)1031
 
12.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_agdrel
Categorical

HIGH CARDINALITY

Distinct273
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
0
939 
1
 
303
2
 
195
3
 
172
Other values (268)
912 

Length

Max length6
Median length1
Mean length1.107984608
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)2.2%

Sample

1st row399712
2nd row960
3rd row559
4th row514
5th row354

Common Values

ValueCountFrequency (%)
*5795
69.7%
0939
 
11.3%
1303
 
3.6%
2195
 
2.3%
3172
 
2.1%
485
 
1.0%
573
 
0.9%
659
 
0.7%
837
 
0.4%
736
 
0.4%
Other values (263)622
 
7.5%

Length

2022-11-06T21:05:44.745681image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0939
 
11.3%
1303
 
3.6%
2195
 
2.3%
3172
 
2.1%
485
 
1.0%
573
 
0.9%
659
 
0.7%
837
 
0.4%
736
 
0.4%
Other values (263)622
 
7.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_noade
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct87
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
1394 
1
 
321
2
 
193
3
 
148
Other values (82)
 
465

Length

Max length4
Median length1
Mean length1.032828283
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.5%

Sample

1st row8820
2nd row1343
3rd row446
4th row3
5th row1

Common Values

ValueCountFrequency (%)
*5795
69.7%
01394
 
16.8%
1321
 
3.9%
2193
 
2.3%
3148
 
1.8%
478
 
0.9%
548
 
0.6%
737
 
0.4%
632
 
0.4%
924
 
0.3%
Other values (77)246
 
3.0%

Length

2022-11-06T21:05:44.921678image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01394
 
16.8%
1321
 
3.9%
2193
 
2.3%
3148
 
1.8%
478
 
0.9%
548
 
0.6%
737
 
0.4%
632
 
0.4%
924
 
0.3%
Other values (77)246
 
3.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_propia
Categorical

HIGH CARDINALITY

Distinct350
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
0
 
480
3
 
244
2
 
149
1
 
146
Other values (345)
1502 

Length

Max length6
Median length1
Mean length1.184102934
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)2.4%

Sample

1st row429713
2nd row2016
3rd row989
4th row517
5th row350

Common Values

ValueCountFrequency (%)
*5795
69.7%
0480
 
5.8%
3244
 
2.9%
2149
 
1.8%
1146
 
1.8%
4121
 
1.5%
582
 
1.0%
665
 
0.8%
754
 
0.6%
845
 
0.5%
Other values (340)1135
 
13.6%

Length

2022-11-06T21:05:45.103679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0480
 
5.8%
3244
 
2.9%
2149
 
1.8%
1146
 
1.8%
4121
 
1.5%
582
 
1.0%
665
 
0.8%
754
 
0.6%
845
 
0.5%
Other values (340)1135
 
13.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_ppagad
Categorical

HIGH CARDINALITY

Distinct340
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
0
 
557
3
 
223
2
 
151
1
 
139
Other values (335)
1451 

Length

Max length6
Median length1
Mean length1.175565176
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique196 ?
Unique (%)2.4%

Sample

1st row321823
2nd row1827
3rd row893
4th row507
5th row342

Common Values

ValueCountFrequency (%)
*5795
69.7%
0557
 
6.7%
3223
 
2.7%
2151
 
1.8%
1139
 
1.7%
4124
 
1.5%
571
 
0.9%
663
 
0.8%
753
 
0.6%
951
 
0.6%
Other values (330)1089
 
13.1%

Length

2022-11-06T21:05:45.291680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0557
 
6.7%
3223
 
2.7%
2151
 
1.8%
1139
 
1.7%
4124
 
1.5%
571
 
0.9%
663
 
0.8%
753
 
0.6%
951
 
0.6%
Other values (330)1089
 
13.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_ppagan
Categorical

HIGH CARDINALITY

Distinct111
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
1923 
1
 
224
2
 
74
3
 
51
Other values (106)
 
249

Length

Max length5
Median length1
Mean length1.031505532
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)0.9%

Sample

1st row86474
2nd row51
3rd row22
4th row4
5th row3

Common Values

ValueCountFrequency (%)
*5795
69.7%
01923
 
23.1%
1224
 
2.7%
274
 
0.9%
351
 
0.6%
427
 
0.3%
720
 
0.2%
617
 
0.2%
N/D15
 
0.2%
513
 
0.2%
Other values (101)157
 
1.9%

Length

2022-11-06T21:05:45.482680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01923
 
23.1%
1224
 
2.7%
274
 
0.9%
351
 
0.6%
427
 
0.3%
720
 
0.2%
617
 
0.2%
n/d15
 
0.2%
513
 
0.2%
Other values (101)157
 
1.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_rentad
Categorical

HIGH CARDINALITY

Distinct115
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size471.4 KiB
*
5795 
0
2031 
1
 
177
2
 
53
3
 
33
Other values (110)
 
227

Length

Max length5
Median length1
Mean length1.03042328
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.0%

Sample

1st row51166
2nd row43
3rd row19
4th row12
5th row12

Common Values

ValueCountFrequency (%)
*5795
69.7%
02031
 
24.4%
1177
 
2.1%
253
 
0.6%
333
 
0.4%
422
 
0.3%
N/D15
 
0.2%
713
 
0.2%
512
 
0.1%
89
 
0.1%
Other values (105)156
 
1.9%

Length

2022-11-06T21:05:45.669679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
02031
 
24.4%
1177
 
2.1%
253
 
0.6%
333
 
0.4%
422
 
0.3%
n/d15
 
0.2%
713
 
0.2%
512
 
0.1%
89
 
0.1%
Other values (105)156
 
1.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_cbiene
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct74
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size471.3 KiB
*
5795 
0
2195 
1
 
119
2
 
39
3
 
20
Other values (69)
 
148

Length

Max length5
Median length1
Mean length1.01996152
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)0.6%

Sample

1st row36611
2nd row14
3rd row20
4th row8
5th row8

Common Values

ValueCountFrequency (%)
*5795
69.7%
02195
 
26.4%
1119
 
1.4%
239
 
0.5%
320
 
0.2%
517
 
0.2%
N/D15
 
0.2%
49
 
0.1%
88
 
0.1%
77
 
0.1%
Other values (64)92
 
1.1%

Length

2022-11-06T21:05:45.858678image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
02195
 
26.4%
1119
 
1.4%
239
 
0.5%
320
 
0.2%
517
 
0.2%
n/d15
 
0.2%
49
 
0.1%
88
 
0.1%
77
 
0.1%
Other values (64)92
 
1.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_sbiene
Categorical

HIGH CARDINALITY

Distinct102
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size471.5 KiB
*
5795 
0
1104 
1
 
400
2
 
214
3
 
132
Other values (97)
671 

Length

Max length5
Median length1
Mean length1.044372294
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)0.6%

Sample

1st row12462
2nd row497
3rd row175
4th row25
5th row15

Common Values

ValueCountFrequency (%)
*5795
69.7%
01104
 
13.3%
1400
 
4.8%
2214
 
2.6%
3132
 
1.6%
4123
 
1.5%
567
 
0.8%
662
 
0.7%
845
 
0.5%
932
 
0.4%
Other values (92)342
 
4.1%

Length

2022-11-06T21:05:46.045680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01104
 
13.3%
1400
 
4.8%
2214
 
2.6%
3132
 
1.6%
4123
 
1.5%
567
 
0.8%
662
 
0.7%
845
 
0.5%
932
 
0.4%
Other values (92)342
 
4.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_radio
Categorical

HIGH CARDINALITY

Distinct336
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
3
 
385
2
 
254
4
 
226
5
 
148
Other values (331)
1508 

Length

Max length6
Median length1
Mean length1.180615681
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)2.4%

Sample

1st row443781
2nd row3561
3rd row1599
4th row364
5th row261

Common Values

ValueCountFrequency (%)
*5795
69.7%
3385
 
4.6%
2254
 
3.1%
4226
 
2.7%
5148
 
1.8%
1111
 
1.3%
696
 
1.2%
784
 
1.0%
855
 
0.7%
1139
 
0.5%
Other values (326)1123
 
13.5%

Length

2022-11-06T21:05:46.238680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3385
 
4.6%
2254
 
3.1%
4226
 
2.7%
5148
 
1.8%
1111
 
1.3%
696
 
1.2%
784
 
1.0%
855
 
0.7%
1139
 
0.5%
Other values (326)1123
 
13.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_tv
Categorical

HIGH CARDINALITY

Distinct342
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size472.6 KiB
*
5795 
3
 
329
2
 
230
0
 
191
4
 
186
Other values (337)
1585 

Length

Max length6
Median length1
Mean length1.173761424
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)2.3%

Sample

1st row479919
2nd row2325
3rd row1226
4th row504
5th row349

Common Values

ValueCountFrequency (%)
*5795
69.7%
3329
 
4.0%
2230
 
2.8%
0191
 
2.3%
4186
 
2.2%
1179
 
2.2%
5135
 
1.6%
681
 
1.0%
764
 
0.8%
859
 
0.7%
Other values (332)1067
 
12.8%

Length

2022-11-06T21:05:46.522681image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3329
 
4.0%
2230
 
2.8%
0191
 
2.3%
4186
 
2.2%
1179
 
2.2%
5135
 
1.6%
681
 
1.0%
764
 
0.8%
859
 
0.7%
Other values (332)1067
 
12.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_video
Categorical

HIGH CARDINALITY

Distinct192
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1000 
1
 
470
2
 
237
3
 
129
Other values (187)
685 

Length

Max length6
Median length1
Mean length1.074555075
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)1.4%

Sample

1st row193496
2nd row433
3rd row244
4th row108
5th row78

Common Values

ValueCountFrequency (%)
*5795
69.7%
01000
 
12.0%
1470
 
5.7%
2237
 
2.8%
3129
 
1.6%
465
 
0.8%
562
 
0.7%
732
 
0.4%
632
 
0.4%
1028
 
0.3%
Other values (182)466
 
5.6%

Length

2022-11-06T21:05:46.683683image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01000
 
12.0%
1470
 
5.7%
2237
 
2.8%
3129
 
1.6%
465
 
0.8%
562
 
0.7%
732
 
0.4%
632
 
0.4%
1028
 
0.3%
Other values (182)466
 
5.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_refri
Categorical

HIGH CARDINALITY

Distinct324
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size472.4 KiB
*
5795 
0
 
358
3
 
272
2
 
240
4
 
188
Other values (319)
1463 

Length

Max length6
Median length1
Mean length1.157527658
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)2.2%

Sample

1st row450367
2nd row1923
3rd row1071
4th row480
5th row325

Common Values

ValueCountFrequency (%)
*5795
69.7%
0358
 
4.3%
3272
 
3.3%
2240
 
2.9%
4188
 
2.3%
1184
 
2.2%
5108
 
1.3%
6104
 
1.3%
766
 
0.8%
845
 
0.5%
Other values (314)956
 
11.5%

Length

2022-11-06T21:05:46.849681image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0358
 
4.3%
3272
 
3.3%
2240
 
2.9%
4188
 
2.3%
1184
 
2.2%
5108
 
1.3%
6104
 
1.3%
766
 
0.8%
845
 
0.5%
Other values (314)956
 
11.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_lavad
Categorical

HIGH CARDINALITY

Distinct272
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size472.0 KiB
*
5795 
0
797 
1
 
354
2
 
299
3
 
153
Other values (267)
918 

Length

Max length6
Median length1
Mean length1.107864358
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)2.1%

Sample

1st row309080
2nd row787
3rd row490
4th row277
5th row183

Common Values

ValueCountFrequency (%)
*5795
69.7%
0797
 
9.6%
1354
 
4.3%
2299
 
3.6%
3153
 
1.8%
491
 
1.1%
562
 
0.7%
643
 
0.5%
739
 
0.5%
836
 
0.4%
Other values (262)647
 
7.8%

Length

2022-11-06T21:05:47.032679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0797
 
9.6%
1354
 
4.3%
2299
 
3.6%
3153
 
1.8%
491
 
1.1%
562
 
0.7%
643
 
0.5%
739
 
0.5%
836
 
0.4%
Other values (262)647
 
7.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_telef
Categorical

HIGH CARDINALITY

Distinct194
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size471.7 KiB
*
5795 
0
1025 
1
 
461
2
 
250
3
 
123
Other values (189)
662 

Length

Max length6
Median length1
Mean length1.068783069
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)1.5%

Sample

1st row223447
2nd row610
3rd row317
4th row99
5th row96

Common Values

ValueCountFrequency (%)
*5795
69.7%
01025
 
12.3%
1461
 
5.5%
2250
 
3.0%
3123
 
1.5%
489
 
1.1%
566
 
0.8%
741
 
0.5%
633
 
0.4%
1121
 
0.3%
Other values (184)412
 
5.0%

Length

2022-11-06T21:05:47.208682image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01025
 
12.3%
1461
 
5.5%
2250
 
3.0%
3123
 
1.5%
489
 
1.1%
566
 
0.8%
741
 
0.5%
633
 
0.4%
1121
 
0.3%
Other values (184)412
 
5.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_boiler
Categorical

HIGH CARDINALITY

Distinct230
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
1183 
1
 
344
2
 
190
3
 
109
Other values (225)
695 

Length

Max length6
Median length1
Mean length1.082611833
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)1.9%

Sample

1st row241185
2nd row791
3rd row415
4th row416
5th row282

Common Values

ValueCountFrequency (%)
*5795
69.7%
01183
 
14.2%
1344
 
4.1%
2190
 
2.3%
3109
 
1.3%
479
 
0.9%
553
 
0.6%
642
 
0.5%
829
 
0.3%
924
 
0.3%
Other values (220)468
 
5.6%

Length

2022-11-06T21:05:47.382683image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
01183
 
14.2%
1344
 
4.1%
2190
 
2.3%
3109
 
1.3%
479
 
0.9%
553
 
0.6%
642
 
0.5%
829
 
0.3%
924
 
0.3%
Other values (220)468
 
5.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vp_autom
Categorical

HIGH CARDINALITY

Distinct258
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size472.1 KiB
*
5795 
1
 
422
0
 
412
2
 
350
3
 
194
Other values (253)
1143 

Length

Max length6
Median length1
Mean length1.119047619
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)1.9%

Sample

1st row263172
2nd row1814
3rd row793
4th row264
5th row160

Common Values

ValueCountFrequency (%)
*5795
69.7%
1422
 
5.1%
0412
 
5.0%
2350
 
4.2%
3194
 
2.3%
4120
 
1.4%
598
 
1.2%
659
 
0.7%
757
 
0.7%
847
 
0.6%
Other values (248)762
 
9.2%

Length

2022-11-06T21:05:47.548679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1422
 
5.1%
0412
 
5.0%
2350
 
4.2%
3194
 
2.3%
4120
 
1.4%
598
 
1.2%
659
 
0.7%
757
 
0.7%
847
 
0.6%
Other values (248)762
 
9.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

tothog
Categorical

HIGH CARDINALITY

Distinct377
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size472.9 KiB
*
5795 
3
 
445
4
 
261
5
 
173
6
 
113
Other values (372)
1529 

Length

Max length6
Median length1
Mean length1.211399711
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)2.6%

Sample

1st row535743
2nd row4757
3rd row2070
4th row579
5th row395

Common Values

ValueCountFrequency (%)
*5795
69.7%
3445
 
5.4%
4261
 
3.1%
5173
 
2.1%
6113
 
1.4%
791
 
1.1%
882
 
1.0%
960
 
0.7%
1054
 
0.6%
1240
 
0.5%
Other values (367)1202
 
14.5%

Length

2022-11-06T21:05:47.710680image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3445
 
5.4%
4261
 
3.1%
5173
 
2.1%
6113
 
1.4%
791
 
1.1%
882
 
1.0%
960
 
0.7%
1054
 
0.6%
1240
 
0.5%
Other values (367)1202
 
14.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

hogjefm
Categorical

HIGH CARDINALITY

Distinct359
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size472.7 KiB
*
5795 
3
 
403
4
 
234
2
 
169
5
 
164
Other values (354)
1551 

Length

Max length6
Median length1
Mean length1.196248196
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)2.5%

Sample

1st row425508
2nd row4429
3rd row1903
4th row501
5th row338

Common Values

ValueCountFrequency (%)
*5795
69.7%
3403
 
4.8%
4234
 
2.8%
2169
 
2.0%
5164
 
2.0%
6119
 
1.4%
789
 
1.1%
881
 
1.0%
946
 
0.6%
1045
 
0.5%
Other values (349)1171
 
14.1%

Length

2022-11-06T21:05:47.885679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
3403
 
4.8%
4234
 
2.8%
2169
 
2.0%
5164
 
2.0%
6119
 
1.4%
789
 
1.1%
881
 
1.0%
946
 
0.6%
1245
 
0.5%
Other values (349)1171
 
14.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

hogjeff
Categorical

HIGH CARDINALITY

Distinct187
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size471.8 KiB
*
5795 
0
905 
1
 
438
2
 
216
3
 
131
Other values (182)
831 

Length

Max length6
Median length1
Mean length1.081048581
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)1.3%

Sample

1st row110235
2nd row328
3rd row167
4th row78
5th row57

Common Values

ValueCountFrequency (%)
*5795
69.7%
0905
 
10.9%
1438
 
5.3%
2216
 
2.6%
3131
 
1.6%
478
 
0.9%
573
 
0.9%
655
 
0.7%
746
 
0.6%
1034
 
0.4%
Other values (177)545
 
6.6%

Length

2022-11-06T21:05:48.043679image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0905
 
10.9%
1438
 
5.3%
2216
 
2.6%
3131
 
1.6%
478
 
0.9%
573
 
0.9%
655
 
0.7%
746
 
0.6%
1034
 
0.4%
Other values (177)545
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pobhog
Categorical

HIGH CARDINALITY

Distinct685
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size474.5 KiB
*
5795 
12
 
84
13
 
79
11
 
65
9
 
57
Other values (680)
2236 

Length

Max length7
Median length1
Mean length1.408369408
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique413 ?
Unique (%)5.0%

Sample

1st row2186099
2nd row15189
3rd row7305
4th row2399
5th row1630

Common Values

ValueCountFrequency (%)
*5795
69.7%
1284
 
1.0%
1379
 
0.9%
1165
 
0.8%
957
 
0.7%
856
 
0.7%
1855
 
0.7%
1054
 
0.6%
1654
 
0.6%
1451
 
0.6%
Other values (675)1966
 
23.6%

Length

2022-11-06T21:05:48.206683image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1284
 
1.0%
1379
 
0.9%
1165
 
0.8%
957
 
0.7%
856
 
0.7%
1855
 
0.7%
1054
 
0.6%
1654
 
0.6%
1451
 
0.6%
Other values (675)1966
 
23.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

phogjefm
Categorical

HIGH CARDINALITY

Distinct657
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size474.3 KiB
*
5795 
12
 
78
11
 
72
8
 
69
10
 
67
Other values (652)
2235 

Length

Max length7
Median length1
Mean length1.39009139
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique408 ?
Unique (%)4.9%

Sample

1st row1790239
2nd row13964
3rd row6754
4th row2115
5th row1424

Common Values

ValueCountFrequency (%)
*5795
69.7%
1278
 
0.9%
1172
 
0.9%
869
 
0.8%
1067
 
0.8%
1366
 
0.8%
963
 
0.8%
1458
 
0.7%
1749
 
0.6%
1648
 
0.6%
Other values (647)1951
 
23.5%

Length

2022-11-06T21:05:48.409678image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
1278
 
0.9%
1172
 
0.9%
869
 
0.8%
1067
 
0.8%
1366
 
0.8%
963
 
0.8%
1458
 
0.7%
1749
 
0.6%
1648
 
0.6%
Other values (647)1951
 
23.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

phogjeff
Categorical

HIGH CARDINALITY

Distinct303
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size472.4 KiB
*
5795 
0
905 
2
 
101
4
 
98
3
 
95
Other values (298)
1322 

Length

Max length6
Median length1
Mean length1.157046657
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)2.1%

Sample

1st row395860
2nd row1225
3rd row551
4th row284
5th row206

Common Values

ValueCountFrequency (%)
*5795
69.7%
0905
 
10.9%
2101
 
1.2%
498
 
1.2%
395
 
1.1%
581
 
1.0%
679
 
0.9%
167
 
0.8%
761
 
0.7%
848
 
0.6%
Other values (293)986
 
11.9%

Length

2022-11-06T21:05:48.612683image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5795
69.7%
0905
 
10.9%
2101
 
1.2%
498
 
1.2%
395
 
1.1%
581
 
1.0%
679
 
0.9%
167
 
0.8%
761
 
0.7%
848
 
0.6%
Other values (293)986
 
11.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Interactions

2022-11-06T21:05:06.807451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:57.728453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:59.268456image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:00.694453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:02.545453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:03.935453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:05.241477image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:06.994455image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:57.979450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:59.475451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:00.899477image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:02.751451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:04.107481image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:05.501451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:07.250450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:58.194447image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:59.659450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:01.200476image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:02.954453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:04.307481image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:05.736448image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:07.505451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:58.423454image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:59.851449image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:01.456450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:03.163450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:04.505450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:05.937454image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:07.718477image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:58.628455image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:00.088451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:01.672450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:03.385453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:04.682475image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:06.162452image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:07.924453image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:58.823476image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:00.305465image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:01.879450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:03.576449image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:04.850449image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:06.389452image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:08.113482image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:04:59.017456image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:00.500451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:02.098451image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:03.748452image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:05.041475image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:05:06.584450image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Correlations

2022-11-06T21:05:48.786682image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-11-06T21:05:49.058706image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-11-06T21:05:49.481686image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-11-06T21:05:49.820706image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-11-06T21:05:50.202709image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-11-06T21:05:10.204657image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-11-06T21:05:13.325647image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-11-06T21:05:14.316645image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

Añoentidadnom_entmunnom_munlocnom_loclongitudlatitudaltitudpobtotpmasculpfemenipob0_4p5_maspob6_14pob12_pob15_pob15_17pob15_24pobf15_49pob18_pmasc18_pfemen18_psdersspcdersspderimsspderistepnacentpnacoentp5_res95p5_reso95pcondiscpcdismotpcdisaudpcdisvispcdismenpcdislenpsindiscp6_14sleep6_14nleep15_alfabp15_analfp5_asiescp5_naescp6_14aescp6_14naescp15_17aescp15_24aescp15_24nescp15_sinstrp15_sprimap15_cprimap15_posprip15_ssecup15_csecup15_sinsecp15_consecp15_cmedssp18_smedsup18_cmedsup18_csupergradoescopsolter12_pcasada12_p5_hlip5_hliynep5_hliyep5_catolicp5_ncatolip5_sinrelipecoactivpecoinactpocupadapocusecppocusecspocusectpocuningrp_1smp1_2smp2_5smp6_10smp10_smpnotrabap_32htrap33_40htrp41_48htrp48_htrtotvivhabvivparhabocuvivparpro_ovppro_ocvpvp_pardesvp_tecdesvp_pisdesvp_ccuartvp2_5cuarvp_2cuarv_1cuartovp_cocgasvp_coclenvp_coccarvp_cocpetvp_sersanvp_aguentvp_drenajvp_electrvp_dreaguvp_dreelevp_aguelevp_agdrelvp_noadevp_propiavp_ppagadvp_ppaganvp_rentadvp_cbienevp_sbienevp_radiovp_tvvp_videovp_refrivp_lavadvp_telefvp_boilervp_automtothoghogjefmhogjeffpobhogphogjefmphogjeff
0200026Sonora0Total de la entidad Sonora0TOTAL DE LA ENTIDADNaNNaNNaN22169691110590110637924461919566174248471617117148206813176942916859478213502996698476804529254811250610101563614463518273793728421862929861204202221046582490997311173721512103717115128314153206506630616161373984742419182200156136271716901912398582431659003691036813035285734174209704793999051212537961834838586702891481556941328530491718889131781216988819969789609810424128736238225415558182825465225895932485177403340301266611904614524030355919808853043552742721860024.141.3720137503894600459754739526882169382244870903362713211149297848305741759550690640208641354447445039971288204297133218238647451166366111246244378147991919349645036730908022344724118526317253574342550811023521860991790239395860
1200026Sonora0Total de la entidad Sonora9998LOCALIDADES DE UNA VIVIENDANaNNaNNaN17933107187215184315970272413802129069993445359411907749844099918767373301991386139071395919044451887512769181725720526391115817101042182025657345544287521164329270036857971694914525181167107847323155483377949254384214158575160981135604808163407508875726194066223517188797867703169305447524695151693.231.7617047937301223330710834512686194917330418601855253912351326135696013432016182751431449735612325433192378761079118144757442932815189139641225
2200026Sonora0Total de la entidad Sonora9999LOCALIDADES DE DOS VIVIENDASNaNNaNNaN891153143597894779211086875652739017331921613738542283502735963416102678819046919848193813264251084318402585772746569288121613227814369161869133323724931221412017286445511442152422464060378243406911315786401527863994259380952124163115931238693743415377176213212100204072963.582.097524415636101350498246130870504143696784913716257198255594469898932219201751599122624410714903174157932070190316773056754551
3200026Sonora1Aconchi0TOTAL MUNICIPALNaNNaNNaN2420126811522382163438182116791444415971535795740153984360110923772121352467308121902313395421591864044033275106334834303927541293229054612931269175737672104840420714886858955856257332240647439124030122015018836210157957423984.181.304353792432813349774005185585325565245225445143517507412825364504108480277994162645795017823992115284
4200026Sonora1Aconchi1ACONCHI1101334.0294930.0600.016478667811631470292124111461003024061046543503974652448891615171449174721612100157226823109252291273175583219472802935107221362029121984212861746271040414291937583650582139258167375727615820912109723194739539216304.161.280353686229757213474500356384363382359358375354135034231281526134978325183962821603953385716301424206
5200026Sonora1Aconchi3ESTANCIA, LA1101243.0294739.0600.0582297285565261194363962910414736718618144012910710576351971250070562103163712583107111213902611180176427921712452321331061582530004762948206230205746359251570719283510914321431425814.091.41071312810822121192000125135130138127129134126213012810087912223119683106781441242058250775
6200026Sonora1Aconchi6RODEO, EL (EL RODEO DE ACONCHI)1101137.0294540.0600.032171503152625458211110284203203102200003050250105033218313161276173179160003100917970210501000144883240.84008040071008887877708800015516506588032320
7200026Sonora1Aconchi7SAN PABLO (SAN PABLO DE ACONCHI)1101154.0294624.0600.014981681712821111105928339652449748341014411280622020139192969201835721930155014195434168411164165000127015754573511111239901066221831301454.831.2201282222023700273029272926272602828000117275292002119302911451423
8200026Sonora1Aconchi10TEPUA (EL CARRICITO)1100420.0294932.0860.06*****************************************************************************1********************************************
9200026Sonora1Aconchi35LOMA, LA1101355.0295018.0600.04*****************************************************************************1********************************************

Last rows

Añoentidadnom_entmunnom_munlocnom_loclongitudlatitudaltitudpobtotpmasculpfemenipob0_4p5_maspob6_14pob12_pob15_pob15_17pob15_24pobf15_49pob18_pmasc18_pfemen18_psdersspcdersspderimsspderistepnacentpnacoentp5_res95p5_reso95pcondiscpcdismotpcdisaudpcdisvispcdismenpcdislenpsindiscp6_14sleep6_14nleep15_alfabp15_analfp5_asiescp5_naescp6_14aescp6_14naescp15_17aescp15_24aescp15_24nescp15_sinstrp15_sprimap15_cprimap15_posprip15_ssecup15_csecup15_sinsecp15_consecp15_cmedssp18_smedsup18_cmedsup18_csupergradoescopsolter12_pcasada12_p5_hlip5_hliynep5_hliyep5_catolicp5_ncatolip5_sinrelipecoactivpecoinactpocupadapocusecppocusecspocusectpocuningrp_1smp1_2smp2_5smp6_10smp10_smpnotrabap_32htrap33_40htrp41_48htrp48_htrtotvivhabvivparhabocuvivparpro_ovppro_ocvpvp_pardesvp_tecdesvp_pisdesvp_ccuartvp2_5cuarvp_2cuarv_1cuartovp_cocgasvp_coclenvp_coccarvp_cocpetvp_sersanvp_aguentvp_drenajvp_electrvp_dreaguvp_dreelevp_aguelevp_agdrelvp_noadevp_propiavp_ppagadvp_ppaganvp_rentadvp_cbienevp_sbienevp_radiovp_tvvp_videovp_refrivp_lavadvp_telefvp_boilervp_automtothoghogjefmhogjeffpobhogphogjefmphogjeff
8306200026Sonora72San Ignacio Río Muerto247SAMUEL VALENZUELA MENDIVIL1101057.0271546.010.05*****************************************************************************2********************************************
8307200026Sonora72San Ignacio Río Muerto248SAN JOSE EL TATA1101614.0272059.05.04*****************************************************************************1********************************************
8308200026Sonora72San Ignacio Río Muerto249LOCALIDAD SIN NOMBRE1101525.0271905.05.02*****************************************************************************1********************************************
8309200026Sonora72San Ignacio Río Muerto250LOCALIDAD SIN NOMBRE1101346.0272115.05.01*****************************************************************************1********************************************
8310200026Sonora72San Ignacio Río Muerto251LOCALIDAD SIN NOMBRE1101402.0272206.010.04*****************************************************************************1********************************************
8311200026Sonora72San Ignacio Río Muerto253LOCALIDAD SIN NOMBRE1101310.0271651.010.04*****************************************************************************1********************************************
8312200026Sonora72San Ignacio Río Muerto254LOCALIDAD SIN NOMBRE1101042.0271826.010.03*****************************************************************************1********************************************
8313200026Sonora72San Ignacio Río Muerto255LOCALIDAD SIN NOMBRE1101042.0271816.010.01*****************************************************************************1********************************************
8314200026Sonora72San Ignacio Río Muerto9998LOCALIDADES DE UNA VIVIENDANaNNaNNaN4362441924738473321302157490287163124229206200535877380420611121413601226240456111814604910258921649209652726316751071852602335293015616315312510173138542201191746671151154363.791.784218342713215832801951621525151255151500018918010382176301191091043638155
8315200026Sonora72San Ignacio Río Muerto9999LOCALIDADES DE DOS VIVIENDASNaNNaNNaN1387167191182398917223784444098403911261211805203001301677615402035517143012351513562877950530621521310631142564239111227810247101732321384.311.9704191319103248002667163542131818000125214125349323021381299